SLSQ427R253

As a Partner Solutions Architect for Europe, you will work with the technical and sales team members who work directly with our customers. You will develop 'technical champions’ within our top Partners, providing enablement on technical matters related to the Databricks product. Working with our partners, you will help our customers achieve tangible, data-driven outcomes through our Databricks Data Intelligence Platform, enabling data teams to complete projects and integrate them into their enterprise Ecosystem. As a member of our team, you will exercise and develop expertise in those areas, using open source projects such as Apache Spark™, MLflow, and Delta Lake, and major public cloud infrastructure and services. the product. You will use this expertise to become a trusted advisor to C&SI partners.

The impact you will have:

• Provide partners with the level of enablement they need to assist their clients in evaluating and adopting Databricks, including hands-on Apache Spark™ programming and integration with the wider cloud ecosystem.

• Engage with the partner technical community by leading workshops, seminars, and meet-ups.

• You will be a big data analytics expert in architecture and design, and will share this knowledge with our partner network.

• Show expertise by producing creative technical solutions and blog posts.

What we look for:

• 8 years of customer-facing experience working with external clients or partners across a variety of industry markets

• Core strength in either data engineering or data science

• Experience demonstrating technical concepts, including presenting and whiteboarding

• Experience developing architectures within a public cloud (AWS, Azure, or GCP)

• Hands-on experience in SQL, Python, Scala, or Java

• Expertise in at least one of the following:

• Data Engineering technologies (Ex, Apache Spark™, Hadoop, Kafka)

• Data Warehousing (Ex, SQL, OLTP/OLAP/DSS)

• Data Science and Machine Learning technologies (Ex, pandas, scikit-learn, HPO)

Qube Research & Technologies (QRT) is a global quantitative and systematic investment manager, operating in all liquid asset classes across the world. We are a technology and data driven group implementing a scientific approach to investing. Combining data, research, technology, and trading expertise has shaped QRT’s collaborative mindset which enables us to solve the most complex challenges. QRT’s culture of innovation continuously drives our ambition to deliver high quality returns for our investors.

We are looking for an exceptional Data Scientist with a strong fixed income background. In this role, you will work between the Research and Trading desks, and the Engineering team to ensure the successful leveraging of data across the firm's fixed income strategies and beyond.

Your future role within QRT

This team is integral to the firm's success. As such, your responsibilities will include:

• Collaborating with Quantitative Researchers and Traders, particularly within fixed income, to design datasets that drive systematic strategies and inform discretionary trading decisions
• Prototyping and designing code to extract, clean, and aggregate data from a wide range of raw sources and formats, including fixed income market data, reference data, and pricing feeds
• Working with Engineers to automate and optimise your code, ensuring robust data extraction processes
• Managing the end-to-end process of onboarding new datasets, with a focus on fixed income instruments such as bonds, rates, credit, and derivatives
• Proactively solving data related problems to minimise time to production
• Innovating and experimenting with novel data extraction methods to enhance the firm's data onboarding toolkit

Your present skillset

• 2+ years of experience as a Data Scientist (or similar position) working with fixed income data; experience in a buy-side quantitative finance role is strongly preferred
• Solid understanding of fixed income markets and instruments including bonds, interest rates, credit, yield curves, or related derivatives
• Postgraduate degree in a quantitative discipline such as Mathematics, Physics or Engineering
• Advanced programming experience in Python, including proficiency with data handling libraries such as Pandas and NumPy
• Proven experience building and managing data pipelines end-to-end; from sourcing and extraction through to cleaning, processing, and delivery
• Excellent communication skills, with the ability to effectively collaborate with all stakeholders, including researchers, traders, engineers, management, and external vendors
• Ability to work in a high-performance, high-velocity environment

QRT is an equal opportunity employer. We welcome diversity as essential to our success. QRT empowers employees to work openly and respectfully to achieve collective success. In addition to professional achievement, we are offering initiatives and programs to enable employees achieve a healthy work-life balance.

Qube Research & Technologies (QRT) is a global quantitative and systematic investment manager, operating in all liquid asset classes across the world. We are a technology and data driven group implementing a scientific approach to investing. Combining data, research, technology, and trading expertise has shaped QRT’s collaborative mindset which enables us to solve the most complex challenges. QRT’s culture of innovation continuously drives our ambition to deliver high quality returns for our investors.

We are looking for an exceptional Data Scientist with strong experience in index data. In this role, you will work between the Research and Trading desks, and the Engineering team to ensure the successful leveraging of index data across the firm's systematic strategies.

Your future role within QRT

This team is integral to the firm's success. As such, your responsibilities will include:

• Collaborating with Quantitative Researchers and Traders to design and maintain index and ETF datasets that drive systematic strategies and inform discretionary trading decisions

• Prototyping and designing code to extract, clean, and aggregate data from a wide range of raw sources and formats, including index constituent data, benchmark compositions, weightings, rebalancing schedules, ETF holdings and flows, and associated reference data

• Working with Engineers to automate and optimise your code, ensuring robust data extraction processes

• Managing the end-to-end process of onboarding new index and ETF datasets, including equity indices, fixed income indices, ETFs, custom baskets, and related benchmark products

• Proactively solving data related problems to minimise time to production

• Innovating and experimenting with novel data extraction methods to enhance the firm's data onboarding toolkit

Your present skillset

• 2+ years of experience as a Data Scientist (or similar position) working with index or ETF data, benchmark data, or index-linked financial products; experience in a buy-side quantitative finance role is strongly preferred

• Solid understanding of index construction, constituent methodology, rebalancing mechanics, ETF structure and flows, and the role of benchmarks in systematic and portfolio-level strategies

• Postgraduate degree in a quantitative discipline such as Mathematics, Physics or Engineering

• Advanced programming experience in Python, including proficiency with data handling libraries such as Pandas and NumPy

• Proven experience building and managing data pipelines end-to-end; from sourcing and extraction through to cleaning, processing, and delivery

• Excellent communication skills, with the ability to effectively collaborate with all stakeholders, including researchers, traders, engineers, management, and external vendors

• Ability to work in a high-performance, high-velocity environment

QRT is an equal opportunity employer. We welcome diversity as essential to our success. QRT empowers employees to work openly and respectfully to achieve collective success. In addition to professional achievement, we are offering initiatives and programs to enable employees achieve a healthy work-life balance.

Qube Research & Technologies (QRT) is a global quantitative and systematic investment manager, operating in all liquid asset classes across the world. We are a technology and data driven group implementing a scientific approach to investing. Combining data, research, technology, and trading expertise has shaped QRT’s collaborative mindset which enables us to solve the most complex challenges. QRT’s culture of innovation continuously drives our ambition to deliver high quality returns for our investors.

We are looking for an exceptional Data Scientist to join the Data Search & Analytics team. In this role, you will work between the Research and Trading desks, and the Engineering team to ensure the successful leveraging of data at the firm.

Your future role within QRT

This team is integral to the firm’s success. As such, your responsibilities will include:

• Collaborating with Quantitative Researchers and Traders to design datasets that drive systematic strategies and to inform discretionary trading decisions
• Prototyping and designing code to extract, clean, and aggregate data from a wide range of raw sources and formats
• Working with Engineers to automate and optimise your code, ensuring robust data extraction processes
• Managing the end-to-end process of onboarding new datasets
• Proactively solving data related problems to minimise time to production
• Innovating and experimenting with novel data extraction methods to enhance the firm’s data onboarding toolkit

Your present skillset

• 3+ years of experience as a Data Scientist (or similar position); experience in a buy-side quantitative finance role is advantageous
• Postgraduate degree in a quantitative discipline such as Mathematics, Physics or Engineering.
• Advanced programming experience in Python, including proficiency with data handling libraries such as Pandas and NumPy
• Demonstratable interest in financial markets and the application of data in its analysis and understanding
• Experience working with both traditional and alternative financial datasets
• Excellent communication skills, with the ability to effectively collaborate with all stakeholders, including researchers, traders, engineers, management, and external vendors
• Ability to work in a high-performance, high-velocity environment

QRT is an equal opportunity employer. We welcome diversity as essential to our success. QRT empowers employees to work openly and respectfully to achieve collective success. In addition to professional achievement, we are offering initiatives and programs to enable employees achieve a healthy work-life balance.

Joining our Customer Data Science team, you’ll work with world class and passionate people to create reusable science modules, ensuring they are productionised, robust and available to the business. You’ll contribute to the research and implementation of new approaches to address complex problems and explore changes to process and tooling to enable research at scale.

What we expect from you

• Experience designing and delivering production-grade analytical Python solutions
• Experience working with relational databases, and SQL-like operations
• Understanding of machine learning techniques such as regularised regression, clustering or tree-based ensembles (and experience applying them with packages like Pandas, sci-kit-learn, SciPy) is highly beneficial
• Experience processing big data, ideally in a Hadoop/Spark environment, would be beneficial
• Proven experience implementing CI/CD and DevOps practices, with the ability to improve deployment reliability, testing standards, and release processes

Responsibilities

• Design, build and own standalone, reusable python packages that surface novel data science solutions, and are fundamental to best-in-class, global products and services
• Build processes and tools to support the research of global science methods, including visual dashboards to showcase their approaches
• Translate stakeholder requirements into robust, production-ready solutions
• Collaborate cross-functionally and mentor junior team members to raise engineering capability and impact

About The Team:

At HelloFresh, we are changing the way people eat forever. We are looking for a Senior Demand Planner to join our Central Planning Team, driving strategic forecasting and technical innovation across the UK and International markets while acting as the operational heartbeat of selected European markets. Seeking a data-savvy pro with strong SQL skills to unlock insights and drive smart decisions!

You will play a pivotal role in our Operations, moving from fragmented local forecasting to a unified, automated, and data-driven global model. You will also own the demand signal that drives every operational decision - from how much food we buy (Procurement) to how many staff we schedule (Production) and how many trucks we book (Logistics).

The Mission:

The Demand Planning team is transitioning from a legacy operating model into a Predictive Intelligence function. Our vision is to evolve from reactive demand estimation to active supply chain shaping, leveraging data to anticipate market shifts, mitigate risk, and optimize operational costs.

You will bridge the gap between legacy operations and predictive intelligence. This role has a critical dual objective:

1. Strategic Architecture & Innovation: Driving the innovation required to architect the standardized forecasting tools, demand simulation frameworks, and future-state processes that will unlock scalable growth across International markets.
2. Operational Execution & Continuity: Ensuring flawless operational continuity for Ireland forecasting, protecting service levels and optimizing costs during this transition.

Ultimately, you will ensure that while we build the next generation of automated planning pipelines, our daily supply chain execution remains agile, accurate, and highly efficient.

What You Will Be Doing:

Strategic Improvement

• Drive Standardization: Establish a unified, model-driven demand planning architecture. You will manage the planning process to strictly limit manual overrides, ensure real-time communication with key stakeholders and proactively take actions to correct the forecast.
• Automated Ecosystem Transition: Drive the shift toward an automated pipeline. Work alongside forecast engineers to design robust solutions that support an efficient, scalable process, ensuring local nuances are handled without breaking the unified code base.
• Scenario Modeling & Innovation: Work with Data Science to refine our Confidence Range Forecasts and Scenario Simulations. Build "What-If" scenarios (e.g., “What if we run an aggressive promo in Ireland next week?”) to stress-test operational capacity and mitigate supply chain risk.

Cross-Functional Stakeholder Management (S&OP)

• Lead the S&OP Rhythm: Facilitate the weekly planning cycle with local stakeholders such as Market leadership, Logistics, Production and Procurement. You will shift the focus from simple error reporting to comprehensive risk management and strategic alignment.
• Commercial & Marketing Alignment: Partner with Marketing to align on customer conversions and retention. You will ensure that growth campaigns are accurately reflected in the Expected Demand view before they hit the supply chain.
• Deep Dive Diagnostics: When deviations occur, you will move beyond surface-level metrics. Your role is to explain the key drivers of the variance to provide actionable insights that prevent recurrence.

Operational Forecasting & Plan Ownership

• Drive the Transition to an Automated Ecosystem: Drive the shift toward an automated, robust ecosystem (using tools like Python, Databricks, and Streamlit as examples). You will not just use these tools; you will work alongside forecast engineers to design robust solutions that support an efficient, scalable process, ensuring local nuances are handled without breaking the unified code base. 
• Own the Number: Generate and validate daily and weekly demand plans for Ireland. You are the guardian of the Decision-Time forecast, ensuring the plan is accurate at the exact moment Procurement and Production need to act, without relying on rigid timelines but rather on operational readiness.
• Manage Trends & Operational Agility: Monitor changes in trends and the need for quick operational adaptations. You will incorporate performance metrics, not only to track stability but to implement stakeholder discipline, ensuring that changes are communicated promptly and the organization adapts efficiently.

Who You Are:

You are a hybrid: part analyst and planner, part diplomat, and part strategic change agent. You know a demand plan is useless if it simply reports numbers without driving action. You ensure every plan reconciles conflicting cross-functional needs, championing structural transformation through deep insights and a proactive understanding of error and risk.

Must-Haves:

• Experience: 4+ years in Demand Planning, Supply Planning, or Data Analytics, preferably in e-commerce, food retail, or FMCG (short shelf-life/perishable experience is a massive plus).
• Tech Stack: You are ready to leave spreadsheets behind. Proficiency in SQL is required. Experience with Python (pandas, forecasting libraries) and Visualization tools (Tableau/Streamlit) is strongly preferred as we transition to our automated pipelines. 
• Analytical Rigor: You possess strong analytical skills and a problem-solving, forward-looking mindset. You understand how to evaluate performance holistically and are proficient in forecasting techniques.
• Young Market Mindset: You are comfortable with ambiguity. You know how to forecast in environments with limited historical data (like our newer markets) by using proxy data and trend smoothing.
• Project Management & Delivery: You can plan and sequence initiatives across markets, handling ambiguity and frequent reprioritisation. You have a track record of prioritising and landing a roadmap of improvements.
• Risk & Change Management: You proactively anticipate demand and supply risks. You are experienced in proposing mitigations (buffers, caps, swaps) and communicating complex trade-offs to senior stakeholders to protect service and cost.
• Project & Data Tools: Advanced Excel/Google Sheets skills are essential. You are comfortable using JIRA/Confluence (or similar) for managing backlogs and requirements.
• Quality & Monitoring: Experience with data validation/QA frameworks, alerting systems, and SLA tracking to ensure forecast reliability.

Soft Skills:

• Influence: You can hold your ground with Senior Stakeholders (Head of Operations, Procurement Directors) when challenging their numbers or explaining a forecast miss.
• Clarity: You can translate complex statistical concepts (e.g., "algorithm bias") into business impact (e.g., "we need to buy 10% more chicken").
• Stakeholder Leadership: You possess strong stakeholder management skills, influencing across Marketing, Procurement, Finance, and Tech. You ensure alignment across diverse functions.

What you will get in return:

● 70% off HelloFresh or Green Chef boxes
● Company pension scheme
● Gym membership
● Bupa private medical insurance (including dental & family cover options)
● Electric vehicle scheme
● Mental health first aiders and an employee assistance programme
● Dog friendly office! (London site only)
● Nursery support scheme
● Cycle to work scheme
● Group Life Assurance

Location: The HelloFresh Farm, 60 Worship Street, EC2A 2EZ, London or any other international HelloFresh market

To be considered for this role, you’ll need to have the independent right to work in the UK, as we're unfortunately unable to provide sponsorship at this time.

Hybrid Working Policy
We offer a hybrid working policy for eligible roles, allowing flexibility to work from home and in the office. For more details on eligibility and how this applies to the role you're applying for, please consult with our recruiter.

Next steps: Your application will be reviewed and if successful, a member of the Talent Acquisition Team will be in touch within 2 weeks. 

The Data Support Developer is responsible for the day-to-day data support of the Sky Road Product Suite.  They will be responsible for front-line (Tier-1) support of all Sky Road clients and processes during European trading hours, Tier-1 and Tier-2 support of client data questions and issues, and developing scripts and tools to facilitate monitoring, alerting, and reconciliation of client data and processes.  The client support team is the front line of support to all Sky Road clients.  The Data Support Developer will communicate with the development team on support issues that require escalation.  They will also work with the project management team to assist with the onboarding of new clients and to understand new client workflows to facilitate support.  The Data Support Developer will also assist with the QA testing process of data workflows during client onboarding and releases.

The Sky Road technology team consists of front-end developers, server-side developers, and data developers. The technology teams closely collaborate with each other, the client services team, and senior management to deliver the latest features into the Sky Road products. This role will ensure the client’s experience is a success.

Key Responsibilities

• Tier-1 support for Sky Road clients during European Trading hours.
• Tier-1 and Tier-2 support for Sky Road client data issues and inquiries.
• Develop scripts and tools to monitor, alert, and reconcile client data and processes.
• Monitor and troubleshoot inbound and outbound data flows.
• Monitor scheduling software, error queues and email for potential support issues.
• Communicate and escalate with the development team on support issues.
• Coordinate with project managers on client onboarding.

Required Qualifications

• Python 3.x experience, at least 2 years.
• Experience with Python packages: Pandas, Numpy, botos, and sqlalchemy.
• Experience with Relational/NoSQL Databases.
• Experience working in a support capacity.
• Strong Excell skills. Must possess the ability to join, pivot and summarize data.
• Ability to troubleshoot support issues.
• Attention to details.
• Experience working in a team environment.

Desired Qualifications

• Understanding of Order Management, Portfolio Management, Compliance and Security Master systems.
• Understanding of core financial data domains including issuers, instruments, industries, ratings, and pricing of financial products.
• Experience with scheduling software.
• Experience with software product support.
• Experience with server-side API frameworks such as REST.

Hudson River Trading (HRT) is seeking curious, thoughtful engineers who enjoy working with data and solving real-world technical problems to join our growing Market Structure Analysis team. In this role as a Quantitative Latency Engineer, you’ll apply data-driven methodologies to understand and optimize trading technology and real-time interactions with financial markets across the globe, spanning traditional and crypto exchanges. No prior finance experience is needed!

Responsibilities 

• Analyze time series network and exchange protocol captures
• Become familiar with the details of specific markets, attend presentations and liaise with exchange counterparts
• Research exchange features, capabilities, and architecture
• Automate collection and visualization of metrics that quantify efficacy of exchange communication
• Formulate and conduct controlled experiments that measure impact of calculated changes to HRT’s trading infrastructure
• Communicate ideas, requirements, and results across disparate teams
• Improve fill rate of our hardware-based trading strategy
• Reduce incidence of cancel-reject responses
• Investigate and report details of various latency-sensitive exchanges

Profile 

• You possess a degree in Data Analytics or a related field
• You can collect and interpret network and/or financial market data
• You have professional experience in latency reduction, preferably in finance
• You have a basic understanding of proprietary trading and exchange technologies

Skills 

• Proficiency in data analytics including statistics, data visualization, and working with large data sets
• Basic understanding of TCP and UDP network protocols
• Extensive experience with Python and relevant data libraries (Pandas, Numpy/Scipy)
• Some familiarity with the details of modern computer systems and networks
• Experience with real time exchange market data and order entry a plus

The estimated base salary range for this position is 200,000 to 300,000 USD per year (or local equivalent). The base pay offered may vary depending on multiple individualized factors, including location, job-related knowledge, skills, and experience. This role will also be eligible for discretionary performance-based bonuses and a competitive benefits package.

Hudson River Trading (HRT) is seeking curious, thoughtful engineers who enjoy working with data and solving real-world technical problems to join our growing Market Structure Analysis team. In this role as a Quantitative Latency Engineer, you’ll apply data-driven methodologies to understand and optimize trading technology and real-time interactions with financial markets across the globe, spanning traditional and crypto exchanges. No prior finance experience is needed! 

Responsibilities

• Contribute directly to impactful improvements to HRT’s low-latency trading systems
• Analyze large datasets to understand how complex systems and networks behave in real-world conditions, such as exchange technology and performance of HRT systems
• Build Python-based tools and scripts to collect, clean, and visualize data in a clear and actionable way
• Design and run experiments to measure the impact of changes and identify opportunities for improvement
• Collaborate closely with HRT’s Algorithm Development, Trading Technology, and Business Development teams to discover, research, and implement improvements to HRT’s architecture
• Liaise with exchanges globally to better understand their technology and stay up to date on changes and improvements

Qualifications

• A technical degree or equivalent practical experience
• Experience with Python and Pandas 
• Proficiency in data analytics including statistics, data visualization, and working with large data sets
• Strong curiosity about how financial systems, networks, and cutting-edge technology work, and a willingness to learn new concepts quickly
• Ability to think analytically, ask insightful questions, and approach unfamiliar problems methodically
• Strong cross-functional communication skills and an interest in collaborating with others

The estimated base salary range for this position is 200,000 to 300,000 USD per year (or local equivalent). The base pay offered may vary depending on multiple individualized factors, including location, job-related knowledge, skills, and experience. This role will also be eligible for discretionary performance-based bonuses and a competitive benefits package.

Hudson River Trading (HRT) is seeking exceptional full-time PhD students to join our Algorithm Development team. Algorithm Developers are responsible for building and maintaining the models that drive our trading. A typical day involves applying rigorous statistical analysis to vast quantities of market and financial data to produce predictive trading models. 

In this role, you will work alongside fellow Algorithm Developers and Software Engineers to research, develop, and test novel order execution and model training methods to increase trading efficiency. This will involve running models live on our high-performance trading infrastructure and analyzing daily performance to maintain ongoing profitability. You can expect to apply your advanced academic research experience and expertise to impactful real world problems in trading across time horizons and machine learning strategies.

Profile

• You’re excited to apply your research expertise to identify new opportunities in worldwide markets  
• You enjoy both self-guided research and collaborating with others to analyze and fix problems efficiently
• You are a critical thinker who can learn and implement new skills in a fast-changing environment

Qualifications

• You are a full-time PhD student in a quantitative discipline (math, physics, computer science, statistics, or a related program) who is eligible for full-time roles in 2026
• Fluency in Python
• Experience with statistical analysis, numerical programming, or machine learning in Python, Pandas/Numpy, R, and/or MATLAB
• Brilliant analytical and problem-solving skills
• Ability to work creatively and independently on long-term technical problems

The estimated base salary for this position is 300,000 USD per year (or local equivalent). The base pay offered may vary depending on multiple individualized factors, including location, job-related knowledge, skills, and experience. This role will also be eligible for discretionary performance-based bonuses and a competitive benefits package.

Hudson River Trading (HRT) is a quantitative trading firm at the forefront of technological innovation. We build and deploy cutting-edge systems within one of the world’s most advanced computing environments to power our global trading operations. Our non-siloed, collaborative coding environment empowers talented engineers to make significant contributions and see their impact daily. At HRT, you'll be challenged to solve the most complex problems in trading alongside many of the brightest minds in the field.

We are seeking highly motivated and skilled Research Engineers who will work very closely with our Algo Developer (Quant Research) trading teams. These roles require exceptional programming fundamentals, a strong user focus, and the ability to thrive in a fast-paced environment with constantly evolving requirements. Multitasking and context switching are inherent aspects of this role, through which you will gain insight into the ideation and execution of some of the world's most sophisticated trading strategies.  

Research Engineers at HRT work on a wide variety of projects. Examples include:

• Designing highly customized quantitative systems that enable Algo Developers to easily express and backtest new predictive signals.
• Building world-class research tooling to speed up Algo Developers’ research iteration.
• Aiding the development and deployment of very large deep learning models for HRT’s live trading.
• Improving HRT’s monetization systems which turn our predictions into profitable trades.
• Evaluating sim vs. live differences to improve the fidelity of our simulations.
• Building systems to monitor and manage live trading.
• Specializing in specific time horizons, from high frequency trading to mid-to-low frequency hedge fund-style strategies.
• Working across a very wide variety of asset classes (from equities to fixed income to options) and regions (from North America to Asia Pacific) – you’ll interact with markets across the world!

Responsibilities

• Design, develop, and maintain robust, performant, and scalable software systems.
• Optimize existing codebases for performance, reliability, and efficiency.
• Debug complex issues across distributed systems in a time-sensitive environment.
• Optimize both the mechanics and ergonomics of Algo Developer research workflows; this requires developing a deep intuition for research methodologies.
• Balance the short term goals of individual trading teams with the longer term goals of HRT’s generalized trading platforms across trading teams. Because we don’t work in a pod environment, REs on different trading teams are expected to share technology and ideas.

Qualifications

• Completed a Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field. If you are currently pursuing your Bachelor's degree, please apply to our Campus/New Grad opportunities.
• Previous experience at a top-tier finance or technology company with an excellent track record of rapid advancement and superlative reviews.
• Experience with supporting internal users is preferred; bonus if you have real hands-on experience with quant research and/or ML/Deep Learning platforms.
• Experience with python numerical, ML and data-oriented libraries is a big plus (e.g. pandas, scikit, pytorch, etc.)
• Candidates should be prepared for technical interviews in either Python or C++. While there is no hard language requirement for RE roles, proficiency in one of these languages will be assessed during the interview process.
• Kindness and empathy is a real requirement. No “smart jerks” at HRT. 
• Strong understanding of data structures, algorithms, and design principles.
• Excellent communication skills, both written and verbal.
• HRT ships every day. The ability to thoughtfully, methodically, and reliably deploy new software and features is a critical skill. 
• If you have management experience, that’s always a bonus – but even so, expect to code!

The estimated base salary range for this position is 200,000 to 300,000 USD per year (or local equivalent). The base pay offered may vary depending on multiple individualized factors, including location, job-related knowledge, skills, and experience. This role will also be eligible for discretionary performance-based bonuses and a competitive benefits package.

For more info about interviewing at HRT, see this blog!

We seek a quantitative researcher to join our Investment Management & Research group. As part of a collaborative quant team, you will partner with portfolio managers, researchers and technologists to implement and operate our core systematic macro strategies.

Your responsibilities will include:

• Researching and backtesting systematic macro trading signals
• Developing and operating trading strategies across a wide range of markets
• Partnering with data engineering and technology teams to build and improve infrastructure

What we are looking for:

• Previous experience (2+ years) working in a systematic macro trading environment, preferably as part of an established quant group trading futures, forwards and related markets
• Data analysis and coding experience (preferably Python/pandas/numpy)
• Strong communication skills with the motivation to work in a large collaborative investment group structure

What You’ll Do:

The Monolith Data Science team is building a layered reliability platform that shifts CoreWeave from reactive troubleshooting to proactive reliability engineering. The platform spans telemetry ingestion, feature engineering, anomaly detection, failure prediction, distributed straggler detection, and agentic root cause analysis. As a forward deployed function, we partner closely with Fleet, Infrastructure, and AI Platform teams to embed data science directly into production environments—improving cluster reliability, increasing effective utilization (MFU), reducing MTTR, and protecting uptime and revenue.

About the role:

As a Forward Deployed Data Scientist, you will work at the intersection of data science and production systems, deploying advanced statistical models and machine learning methodologies directly within operational environments. You will collaborate closely with engineering and infrastructure teams to optimize GPU utilization, workload scheduling, and system efficiency in real time. You will design experiments, analyze large-scale system telemetry data, and build predictive and optimization solutions that are tightly integrated into production workflows. This role blends hands-on deployment with analytical rigor, turning complex infrastructure data into measurable improvements in performance and cost. You will translate research and modeling insights into scalable, production-ready systems.

Who You Are:

• MS or PhD in Computer Science, Statistics, Applied Mathematics, Machine Learning, or related quantitative field
• 8+ years (or equivalent experience) applying statistical modeling or machine learning to large-scale datasets
• Strong proficiency in Python and scientific computing libraries (NumPy, pandas, SciPy, scikit-learn, PyTorch or TensorFlow)
• Demonstrated experience designing and analyzing controlled experiments (A/B testing, causal inference, hypothesis testing)
• Experience working with distributed data systems (Spark, Ray, Dask, or similar)
• Proficiency in SQL and working with large-scale structured datasets
• Experience building, deploying, and maintaining predictive models in production environments
• Strong understanding of optimization techniques (linear programming, convex optimization, stochastic optimization, or reinforcement learning)
• Experience working with time-series data and performance telemetry
• Ability to translate analytical insights into production-ready systems and workflows
• Strong collaboration skills and ability to work cross-functionally in fast-paced environments

Preferred:

• PhD with published research in systems optimization, distributed computing, ML systems, or performance modeling
• Experience with GPU workloads, distributed training, or AI infrastructure
• Familiarity with Kubernetes, containerized workloads, or cloud-native systems
• Experience deploying reinforcement learning or adaptive scheduling systems in production
• Background in capacity planning, forecasting, or resource allocation modeling
• Contributions to open-source ML or systems projects

Wondering if you’re a good fit?
We believe in investing in our people, and value candidates who can bring their own diversified experiences to our teams—even if you aren't a 100% skill or experience match. Here are a few qualities we’ve found compatible with our team. If some of this describes you, we’d love to talk.

• You love uncovering hidden failure patterns in massive, noisy infrastructure datasets
• You enjoy working directly with engineering teams to deploy solutions that have immediate real-world impact
• You’re curious about building autonomous, agentic systems that investigate and explain system behavior
• You’re an expert in reinforcement learning, predictive modeling, or large-scale data analysis

Why CoreWeave?

At CoreWeave, we work hard, have fun, and move fast! We’re in an exciting stage of hyper-growth that you will not want to miss out on. We’re not afraid of a little chaos, and we’re constantly learning. Our team cares deeply about how we build our product and how we work together, which is represented through our core values:

• Be Curious at Your Core
• Act Like an Owner
• Empower Employees
• Deliver Best-in-Class Client Experiences
• Achieve More Together

We support and encourage an entrepreneurial outlook and independent thinking. We foster an environment that encourages collaboration and enables the development of innovative solutions to complex problems. As we get set for takeoff, the organization's growth opportunities are constantly expanding. You will be surrounded by some of the best talent in the industry, who will want to learn from you, too. Come join us!

The starting salary will be determined by job-related knowledge, skills, experience, and the market location. We strive for both market alignment and internal equity when determining compensation. In addition to base salary, our total rewards package includes a discretionary bonus, equity awards, and a comprehensive benefits program (all based on eligibility).

Project Overview

This is a cutting-edge initiative to integrate Large Language Models (LLMs) with WorldQuant's proprietary strategy management tools. The project aims to provide AI-assisted insights, automate routine analytical tasks, and enable natural language interactions for Portfolio Managers to more efficiently analyze, maintain, and enhance their trading strategies. This involves building foundational infrastructure, developing robust data pipelines for metrics and features, and creating a secure, user-centric interface with a strong focus on protecting intellectual property.

The Role:

We are seeking a talented and motivated Full-Time Software Engineer to play a key role in the development and enhancement of this AI-driven platform. You will be responsible for designing, building, and maintaining critical components of the system, primarily focusing on the Model Context Protocol (MCP) servers that form the backbone of the platform. This includes enhancing existing MCPs, such as our proprietary command-line interface for strategy data, developing new MCPs for internal data system integration, strategy analysis, and performance metrics, and contributing to the secure and effective use of LLMs.

Key Responsibilities

• Design, develop, test, and deploy robust and scalable MCP servers and related tools in Python.
• Enhance existing MCPs, including our internal data access tools, to ensure reliable access to strategy metadata, historical PnL data, and PnL attribution by risk factors.
• Develop new MCPs, including but not limited to MCPs for direct data system integration, MCPs for strategy analytics, and MCPs for performance reporting.
• Design and implement secure prompt engineering techniques to interact with LLMs, ensuring effective information retrieval while minimizing the risk of intellectual property leakage.
• Collaborate with project managers, technical leads, and other developers to define technical specifications and integrate various data sources.
• Work on API development and integration, ensuring seamless data flow between different systems (internal knowledge management systems, simulation systems, data warehouses).
• Implement data parsing and manipulation logic for various formats (JSON, CSV).
• Contribute to the design and implementation of data pipelines for strategy metrics and features.
• Address and resolve bugs and issues in existing MCP tools and infrastructure.
• Participate in code reviews, and contribute to unit and integration testing efforts.
• Create and maintain technical documentation for developed components.
• Stay updated with emerging technologies and methodologies in AI, LLMs, prompt engineering, and financial technology.

What You’ll Bring:

Core Skills:

• Strong proficiency in Python programming.
• Proven experience in API development, integration, and consumption.
• Solid understanding of database interaction, data access patterns, and data modeling.
• Experience with data parsing and manipulation libraries and techniques (e.g., pandas, JSON, CSV).
• Understanding of or experience with prompt engineering principles for Large Language Models
• Awareness of data security and intellectual property protection considerations in the context of AI and LLM applications

Domain-Specific Knowledge (Highly Beneficial):

• Familiarity with financial data (e.g., PnL, Sharpe ratio, alpha, risk factors, AUM).
• Experience with quantitative trading systems, market data systems, or strategy management platforms (familiarity with internal data systems or command-line data tools is a significant plus).

Technical Environment Familiarity (Helpful):

• Experience working in a Linux environment.
• Understanding of Command Line Interface (CLI) tools and development.
• Familiarity with version control systems (e.g., Git).

Soft Skills

• Excellent problem-solving and analytical skills.
• Strong collaboration and communication skills, with the ability to work effectively in a team.
• High attention to detail and commitment to delivering high-quality software.
• Ability to learn quickly and adapt to new technologies and complex systems.

Education

• Bachelor's or Master's degree in Computer Science, Engineering

The Role

As a Quant Developer at Man Group you will be part of one of our flagship teams in Man’s systematic trading arm - Man AHL. The team works hand-in-hand with Quant Researchers focusing on equity market neutral models. Your challenges will be varied, and will involve building new alphas and new trading strategies.

The Team

Quant Developers at Man Group are all part of our broader technology team, members of a group of over sixty individuals representing eighteen nationalities. We have varied backgrounds including Computer Science, Mathematics, Physics, Engineering – even Classics - but what unifies us is a passion for technology and writing high-quality code.

Our developers are organised into small cross-functional teams, with our engineering roles broadly of two kinds: “Quant Platform Developers” otherwise known as our “Core Techs”, and “Quant Developers” which we often refer to as “Sector Techs”. We use the term “Sector Tech” because some of our teams are aligned with a particular asset class or market sector. People often rotate teams in order to learn more about our system, as well as find the position that best matches their interests.

 
Our Technology

Our systems are almost all running on Linux and most of our code is in Python, with the full scientific stack: numpy, scipy, pandas, scikit-learn to name a few of the open-source libraries we use extensively. We implement the systems that require the highest data throughput in Java and C++.

We use Airflow for workflow management, Kafka for data pipelines, Bitbucket for source control, Jenkins for continuous integration, Grafana + Prometheus for metrics collection, ELK for log shipping and monitoring, Docker and Kubernetes for containerisation, OpenStack for our private cloud, Ansible and Terraform for architecture automation, and Slack for internal communication. We heavily utilise ArcticDB (https://arcticdb.io/) our in-house developed DataFrame Database. Our technology list is never static: we constantly evaluate new tools and libraries.

 
Technology and Business Skills

At AHL we strive to hire only the brightest and best and most highly skilled and passionate technologists.

Essential

• Exceptional technology skills; recognised by your peers as an expert in your domain
• A keen interest and understanding of financial markets and instruments
• A proponent of strong collaborative software engineering techniques and methods: agile development, continuous integration, code review, unit testing, refactoring and related approaches
• Strong knowledge of Python
• Proficient on Linux platforms with knowledge of various scripting languages
• Experience of data analysis techniques along with relevant libraries e.g. NumPy/SciPy/Pandas
• Relevant mathematical knowledge e.g. statistics, asset pricing theory, optimisation algorithms

Advantageous

• Experience of front office quantitative software development e.g. in a hedge fund or investment bank
• Experience of web based development and visualisation technology for portraying large and complex data sets and relationships
• Experience of machine learning techniques, natural language processing and related libraries and frameworks e.g. scikit-learn, Tensorflow

 
Personal Attributes

• Strong academic record and a degree with high mathematical and computing content e.g. Computer Science, Mathematics, Engineering or Physics from a leading university
• Craftsman-like approach to building software; takes pride in engineering excellence and instils these values in others
• Demonstrable passion for technology e.g. personal projects, open-source involvement
• Intellectually robust with a keenly analytic approach to problem solving
• Self-organised with the ability to effectively manage time across multiple projects and with competing business demands and priorities
• Focused on delivering value to the business with relentless efforts to improve process
• Strong interpersonal skills; able to establish and maintain a close working relationship with quantitative researchers, traders and senior business people alike
• Confident communicator; able to argue a point concisely and deal positively with conflicting views

 
Working Here

Man Group has a small company, no-attitude feel. It is flat structured, open, transparent and collaborative, and you will have plenty of opportunity to grow and have enormous impact on what we do.  We are actively engaged with the broader technology community.

• We host and sponsor London’s PyData and Machine Learning Meetups
• We open-source some of our technology. See github.com/man-group
• We regularly talk at leading industry conferences, and tweet about relevant technology and how we’re using it. See @ManQuantTech

We’re fortunate enough to have a fantastic open-plan office overlooking the River Thames, and continually strive to make our environment a great place in which to work. We believe that agile working allows us to deliver the best business outcomes for our clients and investors as well as having a positive impact on life / work balance and the wellbeing of our staff. We are simultaneously committed to "levelling the playing field" and believe that agile working promotes inclusivity across teams, regions and business units.

• We organise regular social events, everything from photography through climbing, karting, wine tasting and monthly team lunches
• We have annual away days and off-sites for the whole team
• As well as PC’s and Macs, in our office you’ll also find numerous pieces of cool tech such as light cubes and 3D printers, guitars, ping-pong and table-football, and a piano

We offer competitive compensation, a generous holiday allowance, various health and other flexible benefits. We are also committed to continuous learning and development via coaching, mentoring, regular conference attendance and sponsoring academic and professional qualifications.

The Team

The Data and AI division at Man Group is dedicated to ensuring the business can generate valuable insights from data. The division owns the sourcing, delivery and analytics of traditional and alternative data to our investment teams as well developing and supporting Man Group's central data platform. The division is also responsible for development of generative AI tooling to drive innovation and accelerate business processes.

The function seeks to unlock the value in data by partnering with investment teams to source new and diversifying datasets and build scalable evaluation methods and insights on data. The core value which unifies us is a passion to utilise science, technology, and data to enhance our investment and business processes.

The Role

As a Senior Analyst in the Data Science team, you will acquire, wrangle, map and analyse large structured and unstructured datasets to support quantitative research and portfolio management teams in alpha generation. You will act as a subject matter expert on select projects — delivering fundamental research, exploratory analysis and actionable insights. 

Your responsibilities span the full data lifecycle: vendor scoping, data ingestion, exploratory analysis and pipeline prototyping. You will be expected to embrace AI development tools to accelerate delivery and drive adoption across the team. Work is delivered through self-managed projects in collaboration with investment teams and the wider Data & AI division, with the goal of providing scalable, low-touch data delivery and analysis. 

Role Responsibilities

• Collaborate with investment teams to identify data opportunities, propose creative use cases, and recommend datasets to inform investment strategies.
• Acquire, transform and analyse large, messy and unstructured datasets to support investment research and decision-making.
• Research company KPIs, perform statistical tests and draft research reports to maintain an accessible knowledge base for investment teams.
• Contribute to the design and development of our AI-powered data platform, streamlining the data scouting → onboarding → evaluation workflow.
• Build proof-of-concept data products and AI-driven tools, collaborating with technology to productionise them.
• Contribute to firm-wide data initiatives and stay informed on industry trends in alternative data.

Key Competencies

Essential

• 4+ years of proven experience in data wrangling, time-series analysis, statistical techniques and data visualisation.
• Proficient in the Python data science stack (Pandas, NumPy, Spark, Matplotlib) with experience leveraging AI-assisted coding tools to accelerate development.
• Working knowledge of Snowflake, Linux/UNIX, Git, Jira.
• Passion for embracing agentic engineering — willingness and ability to work effectively with AI development tools as part of daily workflow.
• Ability to present technical results and concepts to non-technical audiences.
• Entrepreneurial mindset with a willingness to deeply understand investment strategies and proactively push data-driven solutions.
• Strong academic record with a degree in a STEM field.

Nice to have

• Previous experience working with investment professionals in a fast-paced environment preferred.
• Experience writing ETL pipelines and fluency in SQL preferred.

As a Data Scientist supporting AI engineers, you will partner with one or more engineering teams, developing actionable insights that guide improvements to the Wayve AI Driver. Using experimental and observational analyses of real and simulated driving, you will help teams advance the functionality, safety, and performance of the Wayve AI Driver, helping to advance Wayve as the leader in end-to-end AI for autonomous mobility.

This means you might:

• Formulate and iterate upon the performance metrics that organize our engineering efforts and guide progress toward commercial success
• Design experiments and targeted off-road measurements to ensure that we deliver product requirements to customers while maintaining safety and performance
• Investigate factors in model training and inference leading to bottlenecks in functionality and performance, identifying and validating hypotheses for unlocking improvements

What we are looking for in our candidate

Essential

• 3+ years experience working in a Data Science role.
• Fluent in querying and building large datasets, writing production-level SQL for use in data-transformation pipelines.
• Prior experience designing robust real-world experiments (e.g. A/B) and critically evaluating test-statistics
• Foundations in the fundamentals behind statistics: testing appropriate distributions, testing the assumptions behind frequentist stats
• Proficient in using a statistical scripting language and data science/ML packages (e.g. python such as pandas, sklearn, statsmodels, scipy or R such as dplyr, caret, stats)
• Well-versed in summarising, visualising and communicating findings in an accessible and compelling way
• Track record of influencing team direction through your findings  
• A bias towards deriving actionable insight that can be used to drive prioritisation and strategy for others.
• Comfortable working asynchronously across time zones with cross-functional partners
• You are deeply curious about building something new and relish the idea of helping to define AV2.0 and how we build it.

Desired

• Practical experience with machine learning (e.g. pytorch). Passion to take research ideas to production.
• Track record of promoting statistical rigour and experimental best practices in your prior roles.
• Prior experience using causal inference/econometric techniques and bayesian methodologies for hypothesis testing.
• Prior experience using large datasets with distributed computing (e.g. spark, hadoop or other map-reduce tech)
• Experience working in a fast-moving tech company or startup.

About the Position

We are looking for a Data Engineer to turn messy, real-world datasets into reliable inputs for research and trading. Jane Street depends on data from a wide variety of sources to understand markets and the global economy—think world news, decades of weather patterns, deidentified credit card spending, or packet captures of stock exchange market data feeds. Clean, well-structured data is the difference between noise and a profitable trading signal. 

You'll work closely with trading desks to identify Jane Street's data needs, evaluate datasets, and build pipelines that ingest and transform external data. You'll figure out what data means and how best to represent it. We build our own tools and software when needed, so you'll also help shape the systems you use every day.

This is a collaborative role, but you'll own your work from end to end. It requires a mix of engineering, data analysis, and product sense. You'll develop deep expertise in your data domains and use that understanding to decide what's worth building next.

About You

• Have strong programming skills in any language (Python a plus); you write clear, correct, and maintainable code
• Proficient with SQL or DataFrame libraries like pandas or Polars
• Intellectually curious with a meticulous approach to data investigation; you enjoy the detective work required to make sense of unfamiliar datasets
• A clear and concise communicator
• Fluency in English required

If you're a recruiting agency and want to partner with us, please reach out to agency-partnerships@janestreet.com.

Junior Quant Developer — Backtesting, Simulation & Research, Productionise Research (C++/Python)

Role Overview

We’re hiring a junior Quant Developer to help productionise research into robust, high-performance trading systems. You’ll work closely with Quant Researchers and senior engineers to convert Python research code into production C++, build and optimise backtesting / simulation infrastructure, and support strategy development using L3 market data across multiple venues.

This is a hands-on, engineering-heavy role in a fast-moving environment: you’ll own components end-to-end and contribute directly to research velocity and trading PnL.

Key Responsibilities

• Productionise research models into C++: translate Python prototypes into efficient, maintainable C++ production code.
• Backtesting & simulation: build and improve simulation systems that reflect real market mechanics (order book, fills, cancels, exchange rules).
• L3 market data handling: ingest and process high-volume tick/order-level feeds; create reliable feature pipelines from raw exchange data.
• Performance optimisation: improve latency and throughput of backtests/sims (profiling, memory optimisation, data structures, parallelism where appropriate).
• Research support tooling: create utilities for data inspection, experiment tracking, run orchestration, and post-trade analytics in Python.
• Debugging & correctness: investigate mismatches between simulation and production behaviour; diagnose edge cases and implement fixes with strong test coverage.
• Cross-team collaboration: work daily with researchers and infra/exec engineers to ship improvements from idea → test → production.

Requirements

• Education: Bachelor’s or Master’s from a top university in Computer Science, Engineering, Math, Physics, or similar.
• 0-3 years experience in quantitative finance or other relevant data-intensive industries working with C++
• Strong working knowledge of C++ (memory, ownership, STL, performance-aware coding).
• Experience: demonstrable evidence of hands-on systems work in C++ handling large-scale data (internships, research labs, competitive projects, open-source).
• Comfortable with Python for analysis, tooling, and debugging (pandas/numpy/Jupyter a plus).
• Exposure to quantitative finance, eg through internships/university societies, including market microstructure and L3/order book data.
• Clear “builder mindset”: you like owning problems end-to-end, shipping incrementally, and iterating quickly.

Note: We are currently recruiting for multiple levels and positions, however please only apply for the role that best aligns with your skillset and career goals.

What you will do 

• Work closely with our machine learning engineers, simulation engineers, and customers to translate physics and engineering challenges into mathematical problem formulations.
• Build models to predict the behaviour of physical systems using state-of-the-art machine learning and deep learning techniques.
• Own Research work-streams at different levels, depending on seniority.
• Discuss the results and implications of your work with colleagues and customers, especially how these results can address real-world problems.
• Collaborate with colleagues beyond the research team to translate your models into production-ready code.
• Communicate your work to others internally and externally as called for in paper publication venues, industry workshops, customer conversations, etc. This will involve writing for academic and non-academic audiences.
• Foster a nurturing environment for colleagues with less experience in DS / ML / Stats for them to grow and you to mentor.

What you bring to the table

• Enthusiasm about using machine learning, especially deep learning and/or probabilistic methods, for science and engineering.
• Ability to scope and effectively deliver projects.
• Strong problem-solving skills and the ability to analyse issues, identify causes, and recommend solutions quickly.
• Excellent collaboration and communication skills — with teams and customers alike.
• PhD in computer science, machine learning, applied statistics, mathematics, physics, engineering, or a related field, with particular expertise in any of the following:
  1. operator learning (neural operators), or other probabilistic methods for PDEs;
  2. geometric deep learning or other 3D computer vision methods for point-cloud or mesh-structured data;
  3. generative models for geometry and spatiotemporal data (VAEs, Diffusion Models, Bayesian non-parametric, scaling to large datasets, etc.).
• >2 years of experience in a data-driven role in a professional industry setting (excluding post-doc positions), with exposure to:
  • building machine learning models and pipelines in Python, using common libraries and frameworks (e.g., NumPy, SciPy, Pandas, PyTorch, JAX), especially including deep learning applications;
  • developing models for bespoke problem settings that involve high-dimensional data (spatiotemporal, geometric, physical);
  • iterating on network architectures and model structure, tuning and optimising for inductive biases, improved generalisability, and improved performance;
  • combining theoretical reasoning with empirical intuition to guide investigation;
  • formulating and running experiment pipelines to benchmark models and produce comparable results;
  • writing skills for communication complex technical concepts to peers and non-peers, tailoring the message for the required audience.
• Publication record in reputable venues that demonstrates mastery in your field, and in particular the domains of interest listed above. Desirable venues include (but not limited to): NeurIPS, ICML, ICLR, UAI, AISTATS, AAAI, Siggraph, CVPR or TPAMI/JMLR.

What we offer

Build what actually matters

Help shape an AI-native engineering company at a formative stage, tackling problems that genuinely matter for industry and society. This is work with real-world impact - and something you can be proud to stand behind.

Learn alongside exceptional people

Work with a high-caliber, collaborative team of engineers, scientists, and operators who care deeply about doing great work, and about helping each other get better. We come from diverse backgrounds, but we share a commitment to operating at the highest level and addressing some of the most complex challenges out there. If you’re ambitious, thoughtful, and driven by impact, you’ll feel at home.

Influence over hierarchy

We operate with a flat structure: good ideas win - wherever they come from. Questioning assumptions and challenging the status quo isn’t just welcomed, it’s expected.

Sustainable pace, long-term ambition

Building meaningful technology is a marathon, not a sprint. We believe in balancing focused, ambitious work with a life beyond it. Our hybrid model blends time together in our Shoreditch office with work-from-home days, giving you the flexibility to work sustainably while staying connected in person.

And it doesn’t stop there …

🚀 Equity options - share meaningfully in the company you’re helping to build.

🏦 10% employer pension contribution - because investing in future matters.

🍽️ Free office lunches - to keep you energised and focused.

👶 Enhanced parental leave - 3 months full pay paternity and 6 months full pay maternity leave, to provide extra flexibility during the moments that matter most.

🍼 YellowNest nursery scheme - to help working parents manage childcare costs.

☀️ 25 days of Annual Leave (+ Public Holidays) - because taking time to rest matters.

🏥 Private medical insurance - 100% employee cover, giving you complete peace of mind.

💪 Wellhub Subscription - gain access to thousands of gyms, classes and wellness apps, supporting both physical and mental wellbeing.

👀 Eye tests - because good work depends on good health.

📈 Personal development - dedicated support for learning, development, and leveling up over time.

💛 Employee Assistance Programme (EAP) - confidential wellbeing support, available whenever you need it.

🚲 Bike2Work scheme and 🚆 Season ticket loan - to make getting to work easier and greener.

🚗 Octopus EV salary sacrifice - for a simpler, more sustainable way to drive electric.

🔎 Watch this space, we’re continuing to build this as we grow…

Flow Traders is looking for a Senior Research Engineer to join us in our London office. This is a unique opportunity to join a leading proprietary trading firm with an entrepreneurial and innovative culture at the heart of its business. We value quick-witted, creative minds and challenge them to make full use of their capacities. 

As a Senior Research Engineer, you will be responsible for helping to lead the development of our trading model research framework and using it to conduct research to develop models for trading in production. You'll expand the framework to become global standard way of training, consuming, combining, and transforming any data source in a data-driven systematic way. You will then partner with Quantitative Researchers to build the trading models themselves.

What you will do

• Help to lead the development and global rollout of our research framework for defining and training models through various optimization procedures (supervised learning, backtesting etc.), as well as its integration with our platform for deploying and running those models in production
• Partner with Quantitative Researchers to conduct research: test hypotheses and tune/develop data-driven systematic trading strategies and alpha signals

What you need to succeed

• Advanced degree (Master's or PhD) in Machine Learning, Statistics, Physics, Computer Science or similar
• 8+ years of hands-on experience MLOps, Research Engineering, or ML Research
• A strong background in mathematics and statistics
• Strong proficiency in programming languages such as Python, with experience in libraries like numpy, pytorch, polars, pandas, and ray
• Demonstrated experience in designing and implementing end-to-end machine learning pipelines, including data preprocessing, model training, deployment, and monitoring
• Understanding of and experience with modern software development practices and tools (e.g. Agile, version control, automated testing, CI/CD, observability)
• Understanding of cloud platforms (e. g., AWS, Azure, GCP) and containerization technologies (e. g., Docker, Kubernetes)

Flow Traders does not accept unsolicited resumes from any professional staffing or search firms. All resumes, and any other information identifying potential candidates, submitted to any employee at Flow Traders via-email, the Internet or directly without a valid and signed search agreement will be deemed free to contact by Flow Traders without any restrictions and no placement fee of any kind will be paid in the event the candidate is hired by Flow Traders.

1429 - Associate Director, Analytics - DAT

About WPP Media

WPP is the creative transformation company. We use the power of creativity to build better futures for our people, planet, clients and communities. For more information, visit wpp.com.

WPP Media is WPP’s global media collective. In a world where media is everywhere and in everything, we bring the best platform, people, and partners together to create limitless opportunities for growth. For more information, visit wppmedia.com

About EssenceMediacom: A Leading WPP Media Brand

EssenceMediacom is a new breed of media agency. Grounded in analytics & insights and powered by data & technology, we believe in the power of media and creative to drive breakthroughs for the world’s best brands. We help clients understand the modern marketing paradox and discover the breakthroughs brands need to win with their consumers. We are designed for the new communications economy — built on data & technology, built for people & algorithms, built around diverse schools of thought, built to test & learn at scale, and, crucially, built to evolve.

Role Summary and Impact

We are seeking an Associate Director to join our growing Analytics & Insights team, reporting into the Analytics Director. The team focuses on media effectiveness measurement, campaign analysis and client communication to help make brands become more valuable to the world.

You will be working with leading advertisers, including Airbnb, to harness their data and improve the performance of their campaigns, developing and deploying media measurement solutions. Communication with client stakeholders and effective management of assigned tasks is critical in this role. You will be joining an award winning team, with more than 16 tech and media industry awards to our name, including Campaign Magazine’s Tech Awards Agency of the Year, Best Use of AI, and Breakthrough Tech as Part of a Campaign awards.

We have invested in giving you the tools to make you as successful as possible, including training/development, full access to Google Cloud Platform and a wider global community of analysts and data scientists.

Some of the things we'd like you to do

• Build and apply a deep understanding of marketing objectives to support Account teams with comprehensive measurement and testing plans.
• To help deliver “best in class” analytical capabilities across the agency with the wider Analytics team, including the use of new methods, techniques, tools and systems. Managing the process through to delivery and taking ownership of global roll out. 
• Recruit, manage, and develop a team of 1-3 analysts, ensuring high-quality output and efficient workflow.
• Lead the creation of clear, robust and thought-provoking campaign reviews and insights, and show the wider team/clients how to improve effectiveness. 
• Develop deep understanding of marketing platform testing and targeting abilities, and act in a consultative capacity in their implementation
• Deliver insightful campaign reviews with actionable recommendations to improve marketing effectiveness.
• Provide actionable insights and design experiments to optimise campaign performance - focusing on brand and conversion lift studies.
• Be a reliable day-to-day point of contact for clients and maintain robust client relationships.
• Coordinate with third-party vendors for the assessment and management of bespoke measurement solutions, including contracts and SOWs.
• Manage relationships with data engineering teams and set automation strategies to integrate new tools and solutions.
• Translate complex data concepts for stakeholders and contribute to the company's data strategy, promoting data-driven innovation within the media industry.

Skills and Experience

At WPP Media, we believe in the power of our culture and our people. It’s what elevates us to deliver exceptional experiences for both our clients and each other. In this role it will be critical to embrace WPP & WPP Media’s shared core values:

• Be Extraordinary by Leading Collectively to Inspire transformational Creativity.
• Create an Open environment by Balancing People and Client Experiences by Cultivating Trust.
• Lead Optimistically by Championing Growth and Development to Mobilize the Enterprise.

• You will be highly numerate: able to confidently interpret data and apply statistical tests to draw robust conclusions. Holding a degree(s) in a quantitative field: Statistics, Mathematics, Economics, Engineering, Physical Science or Computer Science
• Experience in analytics, measurement, data science, or a related field
• Knowledge of applying measurement to media campaigns through Meta/Google, through brand and conversion lift studies, matched market tests or otherwise
• Well developed problem-solving skills and the ability to think critically and creatively
• Strong understanding of statistics including hypothesis testing, descriptive statistics and distribution theory
• Strong communication skills, with the ability to present complex ideas to both technical and non-technical audiences
• Able to work independently and as part of a cross-functional team, using project management tools such as Jira/Trello. Ability to project manage analytics projects.
• Highly capable at presenting data in a visually engaging and insightful manner that cuts through the noise
• Experience in mentorship and management, ability to display empathy in difficult situations and lead by example
• Stay up-to-date with the latest industry trends and advancements in data science and analytics
• Proficiency in SQL & R/Python, including understanding of packages such as pandas, numpy, scipy & matplotlib. 
• Strong understanding of what data points can be collected and analysed in a digital campaign, and how each data point should be analysed. Including knowledge of media data and incremental measurement, including both Direct Response and Brand campaigns

Nice to haves:

• Experience with digital ad technologies (SA360, GA, Campaign Manager, DV360, Meta Business Manager), site analytics and tools
• Experience with cloud technologies, such as GCP
• Proven understanding and experience with digital ad platforms APIs
• Knowledge of market research methodologies
• Speaking any European languages

Life at WPP Media & Benefits

Our passion for shaping the next era of media includes investing in our employees to help them do their best work, and we’re just as committed to employee growth as we are to responsible media investment. WPP Media employees can tap into the global WPP Media & WPP networks to pursue their passions, grow their networks, and learn at the cutting edge of marketing and advertising. We have a variety of employee resource groups and host frequent in-office events showcasing team wins, sharing thought leadership, and celebrating holidays and milestone events. Our benefits include competitive medical, group retirement plans, vision, and dental insurance, significant paid time off, preferential partner discounts, and employee mental health awareness days.  

WPP Media is an equal opportunity employer and considers applicants for all positions without discrimination or regard to particular characteristics. We are committed to fostering a culture of respect in which everyone feels they belong and has the same opportunities to progress in their careers.

We believe the best work happens when we're together, fostering creativity, collaboration, and connection. That's why we’ve adopted a hybrid approach, with teams in the office around four days a week. If you require accommodations or flexibility, please discuss this with the hiring team during the interview process.

Please note this is a UK based role and requires individuals to have the right to work in this location

Please read our Privacy Notice (https://www.wppmedia.com/pages/privacy-policy) for more information on how we process the information you provide.

#LI-Promoted

As a Data Scientist supporting AI engineers, you will partner with one or more engineering teams, developing actionable insights that guide improvements to the Wayve AI Driver. Using experimental and observational analyses of real and simulated driving, you will help teams advance the functionality, safety, and performance of the Wayve AI Driver, helping to advance Wayve as the leader in end-to-end AI for autonomous mobility.

This means you might:

• Formulate and iterate upon the performance metrics that organize our engineering efforts and guide progress toward commercial success
• Design experiments and targeted off-road measurements to ensure that we deliver product requirements to customers while maintaining safety and performance
• Investigate factors in model training and inference leading to bottlenecks in functionality and performance, identifying and validating hypotheses for unlocking improvements

What we are looking for in our candidate

Essential

• 3+ years experience working in a Data Science role.
• Fluent in querying and building large datasets, writing production-level SQL for use in data-transformation pipelines.
• Prior experience designing robust real-world experiments (e.g. A/B) and critically evaluating test-statistics
• Foundations in the fundamentals behind statistics: testing appropriate distributions, testing the assumptions behind frequentist stats
• Proficient in using a statistical scripting language and data science/ML packages (e.g. python such as pandas, sklearn, statsmodels, scipy or R such as dplyr, caret, stats)
• Well-versed in summarising, visualising and communicating findings in an accessible and compelling way
• Track record of influencing team direction through your findings  
• A bias towards deriving actionable insight that can be used to drive prioritisation and strategy for others.
• Comfortable working asynchronously across time zones with cross-functional partners
• You are deeply curious about building something new and relish the idea of helping to define AV2.0 and how we build it.

Desired

• Practical experience with machine learning (e.g. pytorch). Passion to take research ideas to production.
• Track record of promoting statistical rigour and experimental best practices in your prior roles.
• Prior experience using causal inference/econometric techniques and bayesian methodologies for hypothesis testing.
• Prior experience using large datasets with distributed computing (e.g. spark, hadoop or other map-reduce tech)
• Experience working in a fast-moving tech company or startup.

Note: We are currently recruiting for multiple positions across different levels, however please only apply for the role that best aligns with your skillset and career goals.

What you will do 

• Work closely with our research scientists and simulation engineers to build and deliver models that address real-world physics and engineering problems.
• Design, build and optimise machine learning models with a focus on scalability and efficiency in our application domain.
• Transform prototype model implementations to robust and optimised implementations.
• Implement distributed training architectures (e.g., data parallelism, parameter server, etc.) for multi-node/multi-GPU training and explore federated learning capacity using cloud (e.g., AWS, Azure, GCP) and on-premise services.
• Work with research scientists to design, build and scale foundation models for science and engineering; helping to scale and optimise model training to large data and multi-GPU cloud compute.
• Identify the best libraries, frameworks and tools for our modelling efforts to set us up for success.
• Own Research work-streams at different levels, depending on seniority.
• Discuss the results and implications of your work with colleagues and customers, especially how these results can address real-world problems.
• Work at the intersection of data science and software engineering to translate the results of our Research into re-usable libraries, tooling and products.
• Foster a nurturing environment for colleagues with less experience in ML / Engineering for them to grow and you to mentor.

What you bring to the table

• Enthusiasm about developing machine learning solutions, especially deep learning and/or probabilistic methods, and associated supporting software solutions for science and engineering.
• Ability to work autonomously and scope and effectively deliver projects across a variety of domains.
• Strong problem-solving skills and the ability to analyse issues, identify causes, and recommend solutions quickly.
• Excellent collaboration and communication skills — with teams and customers alike.
• MSc or PhD in computer science, machine learning, applied statistics, mathematics, physics, engineering, software engineering, or a related field, with a record of experience in any of the following:
  
  • Scientific computing;
  • High-performance computing (CPU / GPU clusters);
  • Parallelised / distributed training for large / foundation models.
• Ideally >2 years of experience in a data-driven role in a professional setting, with exposure to:
  • scaling and optimising ML models, training and serving foundation models at scale (federated learning a bonus);
  • distributed computing frameworks (e.g., Spark, Dask) and high-performance computing frameworks (MPI, OpenMP, CUDA, Triton);
  • cloud computing (on hyper-scaler platforms, e.g., AWS, Azure, GCP);
  • building machine learning models and pipelines in Python, using common libraries and frameworks (e.g., NumPy, SciPy, Pandas, PyTorch, JAX), especially including deep learning applications;
  • C/C++ for computer vision, geometry processing, or scientific computing;
  • software engineering concepts and best practices (e.g., versioning, testing, CI/CD, API design, MLOps);
  • container-ization and orchestration (Docker, Kubernetes, Slurm);
  • writing pipelines and experiment environments, including running experiments in pipelines in a systematic way.

What we offer

Build what actually matters

Help shape an AI-native engineering company at a formative stage, tackling problems that genuinely matter for industry and society. This is work with real-world impact - and something you can be proud to stand behind.

Learn alongside exceptional people

Work with a high-caliber, collaborative team of engineers, scientists, and operators who care deeply about doing great work, and about helping each other get better. We come from diverse backgrounds, but we share a commitment to operating at the highest level and addressing some of the most complex challenges out there. If you’re ambitious, thoughtful, and driven by impact, you’ll feel at home.

Influence over hierarchy

We operate with a flat structure: good ideas win - wherever they come from. Questioning assumptions and challenging the status quo isn’t just welcomed, it’s expected.

Sustainable pace, long-term ambition

Building meaningful technology is a marathon, not a sprint. We believe in balancing focused, ambitious work with a life beyond it. Our hybrid model blends time together in our Shoreditch office with work-from-home days, giving you the flexibility to work sustainably while staying connected in person.

And it doesn’t stop there …

🚀 Equity options - share meaningfully in the company you’re helping to build.

🏦 10% employer pension contribution - because investing in future matters.

🍽️ Free office lunches - to keep you energised and focused.

👶 Enhanced parental leave - 3 months full pay paternity and 6 months full pay maternity leave, to provide extra flexibility during the moments that matter most.

🍼 YellowNest nursery scheme - to help working parents manage childcare costs.

☀️ 25 days of Annual Leave (+ Public Holidays) - because taking time to rest matters.

🏥 Private medical insurance - 100% employee cover, giving you complete peace of mind.

💪 Wellhub Subscription - gain access to thousands of gyms, classes and wellness apps, supporting both physical and mental wellbeing.

👀 Eye tests - because good work depends on good health.

📈 Personal development - dedicated support for learning, development, and leveling up over time.

💛 Employee Assistance Programme (EAP) - confidential wellbeing support, available whenever you need it.

🚲 Bike2Work scheme and 🚆 Season ticket loan - to make getting to work easier and greener.

🚗 Octopus EV salary sacrifice - for a simpler, more sustainable way to drive electric.

🔎 Watch this space, we’re continuing to build this as we grow…

Note: We are currently recruiting for multiple positions across different levels, however please only apply for the role that best aligns with your skillset and career goals.

What you will do 

• Shape Research group strategy and culture in a significant way, especially in domains of expertise.
  • Be opinionated and formulate strategy on engineering topics relevant to our Research priorities, especially on: scaled engineering, securing compute, infrastructure stack.
  • Define necessary profiles to execute this strategy.
  • Promote effective working patterns and proactively flag issues with team dynamics to foster a productive environment.
  • Nurture younger colleagues to grow their skillset and guide their professional development.
• Own Research work-streams at a high-level to deliver outcomes.
  • Align priorities with problem stakeholders, internal and external.
  • Set the technical direction for the stream and apply judgement and taste to drive progress.
  • Plan roadmaps with clear milestones for key decisions and outcomes.
  • Organise and guide the more junior members of the team to effectively execute and deliver against this roadmap.
  • Communicate purpose and key outcomes to raise awareness across the company and create opportunities for use and deployment.
• The below activities in particular.
  • Work closely with our research scientists and simulation engineers to build and deliver models that address real-world physics and engineering problems.
  • Design, build and optimise machine learning models with a focus on scalability and efficiency in our application domain.
  • Transform prototype model implementations to robust and optimised implementations.
  • Implement distributed training architectures (e.g., data parallelism, parameter server, etc.) for multi-node/multi-GPU training and explore federated learning capacity using cloud (e.g., AWS, Azure, GCP) and on-premise services.
    • Work with research scientists to design, build and scale foundation models for science and engineering; helping to scale and optimise model training to large data and multi-GPU cloud compute.
  • Identify the best libraries, frameworks and tools for our modelling efforts to set us up for success.
  • Discuss the results and implications of your work with colleagues and customers, especially how these results can address real-world problems.
  • Work at the intersection of data science and software engineering to translate the results of our Research into re-usable libraries, tooling and products.
  • Foster a nurturing environment for colleagues with less experience in ML / Engineering for them to grow and you to mentor.

What you bring to the table

• Enthusiasm about developing machine learning solutions, especially deep learning and/or probabilistic methods, and associated supporting software solutions for science and engineering.
• Ability to work autonomously and scope and effectively deliver projects across a variety of domains.
• Strong problem-solving skills and the ability to analyse issues, identify causes, and recommend solutions quickly.
• Excellent collaboration and communication skills — with teams and customers alike.
• MSc or PhD in computer science, machine learning, applied statistics, mathematics, physics, engineering, software engineering, or a related field, with a record of experience in any of the following:
  • scientific computing;
  • high-performance computing (CPU / GPU clusters);
  • parallelised / distributed training for large / foundation models.
•  4 years of experience in a data-driven role in a professional industry setting, where you have been instrumental in most of the below:
  • • scaling and optimising ML models, training and serving foundation models at scale (federated learning a bonus);
    • employing distributed computing frameworks (e.g., Spark, Dask) and high-performance computing frameworks (MPI, OpenMP, CUDA, Triton);
    • employing cloud computing (on hyper-scaler platforms, e.g., AWS, Azure, GCP);
    • building machine learning models and pipelines in Python, using common libraries and frameworks (e.g., NumPy, SciPy, Pandas, PyTorch, JAX), especially including deep learning applications;
    • building or using C/C++ for computer vision, geometry processing, or scientific computing;
    • following and promoting software engineering concepts and best practices (e.g., versioning, testing, CI/CD, API design, MLOps);
    • container-izing and orchestrating compute tasks (Docker, Kubernetes, Slurm);
    • writing pipelines and experiment environments, including running experiments in pipelines in a systematic way.

What we offer

Build what actually matters

Help shape an AI-native engineering company at a formative stage, tackling problems that genuinely matter for industry and society. This is work with real-world impact - and something you can be proud to stand behind.

Learn alongside exceptional people

Work with a high-caliber, collaborative team of engineers, scientists, and operators who care deeply about doing great work, and about helping each other get better. We come from diverse backgrounds, but we share a commitment to operating at the highest level and addressing some of the most complex challenges out there. If you’re ambitious, thoughtful, and driven by impact, you’ll feel at home.

Influence over hierarchy

We operate with a flat structure: good ideas win - wherever they come from. Questioning assumptions and challenging the status quo isn’t just welcomed, it’s expected.

Sustainable pace, long-term ambition

Building meaningful technology is a marathon, not a sprint. We believe in balancing focused, ambitious work with a life beyond it. Our hybrid model blends time together in our Shoreditch office with work-from-home days, giving you the flexibility to work sustainably while staying connected in person.

And it doesn’t stop there …

🚀 Equity options - share meaningfully in the company you’re helping to build.

🏦 10% employer pension contribution - because investing in future matters.

🍽️ Free office lunches - to keep you energised and focused.

👶 Enhanced parental leave - 3 months full pay paternity and 6 months full pay maternity leave, to provide extra flexibility during the moments that matter most.

🍼 YellowNest nursery scheme - to help working parents manage childcare costs.

☀️ 25 days of Annual Leave (+ Public Holidays) - because taking time to rest matters.

🏥 Private medical insurance - 100% employee cover, giving you complete peace of mind.

💪 Wellhub Subscription - gain access to thousands of gyms, classes and wellness apps, supporting both physical and mental wellbeing.

👀 Eye tests - because good work depends on good health.

📈 Personal development - dedicated support for learning, development, and leveling up over time.

💛 Employee Assistance Programme (EAP) - confidential wellbeing support, available whenever you need it.

🚲 Bike2Work scheme and 🚆 Season ticket loan - to make getting to work easier and greener.

🚗 Octopus EV salary sacrifice - for a simpler, more sustainable way to drive electric.

🔎 Watch this space, we’re continuing to build this as we grow…

Who You Are:

We are seeking a skilled Python developer to join our dynamic Financial Engineering team; where you'll build innovative reporting solutions that drive key financial decisions. This is a unique opportunity to work at the intersection of technology and finance, tackling complex challenges in a fast-paced, impact-driven environment.

You should have a strong background in software development, expert level knowledge of SQL, and a good understanding of crypto trading.

You should have the ability to work independently, have strong analytical and problem-solving skills, with a desire to own issues and see them through to resolution.

What You’ll Do:

• Collaborate with the Finance Engineering team to maintain and enhance existing solutions
• Work with internal Finance and Accounting clients to develop new solutions
• Provide first-line support to internal clients. This involves dealing with queries from clients and identifying and resolving issues
• Contribute to new Finance Engineering initiatives

What We’re Looking For:

• Excellent programming skills in Python and strong working knowledge of Pandas and PySpark libraries
• Excellent knowledge of relational databases and SQL
• Experience with integration of multiple platforms
• Experience with ETL processes
• Experience providing first-line support for business clients
• Full SDLC process experience
• Excellent communications skills, both written and verbal

Bonus Points: 

• Technical experience with Databricks or any similar Delta Lake platforms
• Experience working with large datasets
• Experience with AWS cloud deployments and API
• Experience with Docker and Kubernetes
• Experience with Go, C#, or Java.
• Familiarity with financial statements (e.g. balance sheets, income statements / PnL).
• Familiarity with Crypto trading (spot, DeFi, and derivatives)

What We Offer:

• Competitive base salary and discretionary bonus
• Company-paid health and protective benefits for employees and their eligible dependents
• Free virtual coaching and counseling sessions
• Opportunities to learn about the Crypto industry
• Smart, entrepreneurial, and fun colleagues
• Employee Resource Groups

*Benefits may vary depending on location.

The opportunity:

You will support senior colleagues in achieving the efficient delivery of client projects. Typical responsibilities and duties are the collection and preparation of data, contributing to the finalisation of models, writing results and implications and SFX creation.

Your role as Principal Analyst is to take responsibility for and oversee other analysts. You will also be expected support the development of analysts through the Training Academy, Knowledge Shares and feedback. Principal Analysts should develop relationships with their counterparts client side and be able to communicate Gain Theory approaches and brand beliefs.

What you’ll be doing:

Working with data: Data extraction and manipulation, data analysis and validation, batch files, programming

• Undertake data extraction, manipulation, and data analysis to understand the marketplace and client context relevant to each project.
• Analyse all datasets to ensure that each KPI is understood and can be explained back to the team.
• Ensure that all tables, charts and other information produced by you, or others has been checked for accuracy and formatted to GT standards before passing on to senior project team.
• Be responsible for data collection including preparation and sending of data requests, chasing outstanding data and querying data with clients and agencies.
• Ensure that ROVA input files are structured to meet requirements of project (e.g. order and number of variables, exclusion of unnecessary variables)
• Ensure that all outputs are checked for accuracy by analysts; record any checks made.
• Proficiency in using data extraction tools (i.e. Advantage, AdDynamix, Sysomos, Google Trends, Google Analytics, Double Click) and able to teach others in their use. Be aware of alternatives and the PROs / CONs of the tool.
• Proficiency in using Excel/SQL/Python/Pandas/Analytics Workbench to process, transform, create variables and build models. Be or be working towards expert knowledge in a selection of these tools / approaches.

Building Models: Model building and validation, sales effects calculations, ROIs, media optimisation

• Oversee the building of comprehensive base models according to the project specification, incorporating all drivers of KPIs, providing rationale for variables entered, understanding coefficients and SFX.
• Taking base models, oversee or build in additional improvements and progress the model towards finalization.
• Calculate sales effects throughout the project to check results and assess their correctness, i.e. does media contribution make sense? Report to project team on preliminary findings and observations
• Create sales effect/ ROI workbook, ensure it is easy to follow and all links are correct.
• Create response curves and optimisation spreadsheets or alternatively use available tools for budget allocation. Run scenarios required to answer client objectives.
• Validate models, identify areas of weakness, suggest and test possible improvements and ensure robustness and validity.

.Creation of presentations: Content creation, summary of findings, accuracy checks

• Create content as specified by project lead, taking responsibility for entire sections rather than focusing on just factual and data slides.
• Assist in the creation of all areas of the deck as directed.
• Ensure that all content is checked for accuracy and that it is correctly labelled, complete and ready for delivery to client.
• Summarise and comment on findings, add consultancy input rather than on factual statements.
• Be able to explain and justify any potential changes that need to be made to provide sensible results. Especially important when reviewing others’ outputs that you are overseeing.

 Client Relationship Management & Interaction: Client contact and interaction, delivery of results to the client

• Answer specific data questions that may arise in external meetings as the lead analyst; act as a specialist closest to the data.
• Be prepared to lead calls with clients (data calls, weekly calls etc.).
• Be involved in the delivery of results to the client and present sections of presentations during meetings.
• Take charge of day-to-day client contact using email and telephone where appropriate.

 Interpretation of results: Result interpretation and rationale, recommendations, translation of results from analytics into actionable recommendations

• Provide input into the results and implications and comment on the interpretation for future strategies.
• Interpret results and understand the implications of these results to the client. Be able to explain your interpretation to the team and defend your POV.
• Be able to explain and justify any potential changes that need to be made to provide sensible results. Especially important when reviewing others’ outputs that you are overseeing.

 Team Support & Development: Team collaboration, leadership, communication

• Motivate and inspire team members by ensuring that excellent performance is acknowledged and reasons for success are shared amongst the team.
• Take responsibility for supervising, supporting and training junior team members.
• Take responsibility for training new joiners including project managing Graduate Analysts during their training project.
• Lead by behaving in a way that reinforces values and goals of Gain Theory to all employees.
• Assist team members in interpreting the tasks they have been set.
• Provide timely feedback to team members.

Innovation: Process improvements, product development, new trainings

• Actively seek more efficient ways of doing things for yourself and others and turn suggestions into actions.
• Host knowledge shares to share your experience on topics of interest for the business.
• Be proactive in using new tools and take the active part in their testing when in the development stage, in line with your personal expertise and skills.
• Assist in service and product development, where necessary. Actively put yourself forward if your involvement can improve outcomes for the company.

What we want from you:

• 2-3 years of experience in an analytical role, preferably within marketing analytics, consulting, or a related field.
• Deep understanding of analytical and modeling methodologies, including MMM, attribution, econometrics, and other advanced techniques.
• You can work within an inclusive and diverse team to deliver fresh thinking and innovative solutions. 
• You interact with colleagues and with our clients in a way that strengthens our culture of inclusivity, diversity, care, growth and recognition.
• You are tenacious, hardworking, curious and have a strong ability to communicate.
• You demonstrate a positive desire and strong aptitude for making data informed decisions.
• You can demonstrate good problem-solving skills and understanding of consumer behaviour.
• You have the capacity to work and learn quickly in a fast-paced environment.
• You take keen interest in your own learning and development.
• You demonstrate behaviours which support our values.
• Strong strategic thinking and problem-solving skills.
• Excellent communication, presentation, and stakeholder management skills.
• Proven project management experience, with the ability to manage multiple projects simultaneously.
• Proficiency in statistical software packages (e.g., R, Python) and data visualization tools.
• Bachelor's or Master's degree in a quantitative field (e.g., Statistics, Economics, Mathematics).

Why work for us? 

Gain Theory is committed to actively building a diverse, equitable and inclusive workplace where everyone feels welcomed, valued and heard, and is treated with dignity and respect.  As leaders and creative partners across industries, it is our responsibility to cultivate an environment reflective of our greatest asset; our people. We believe that this commitment inspires growth and delivers equitable outcomes for everyone as well as the clients and communities we serve. 

What we pride ourselves on: 

• Growth and development
• Meaningful work
• Flexible by design
• Brilliant benefits 
• Culture with Heart 
  
  

Our exceptional and skilled team defines Gain Theory. That's why we seek individuals who strive for excellence and continually challenge us to improve.

What we do 

Gain Theory is a global marketing effectiveness and foresight consultancy. Our vision is to accelerate growth for ambitious brands by giving clients the confidence to make better data-informed investment decisions. High-touch consultancy powered by unique partnerships and proprietary technology are used to power our award-winning solutions.  

 As a WPP consultancy, Gain Theory also has access to a range of data, expertise, and tools that create a truly differentiated offering. 

 Gain Theory is a WPP agency (NYSE: WPP).      

 Who we are 

We are a people-centric organisation whose culture is underpinned by 4 important values: Be Curious, Be Positive, Make it Better and Act with Consideration. We channel these values through our behaviours, in the way we work, and in the interactions we have with each other and our clients. 

The Role

Join our dynamic Core Technology team as a Software Developer, where you'll play a crucial role in building and enhancing the software that drives both our Asset Management and Securities businesses. You’ll work closely with Operations, Treasury, Risk, Compliance, Finance, and Client Services—embedded alongside these teams to deeply understand their challenges and anticipate their needs.

You’ll also collaborate with trading teams to ensure new strategies and markets are fully supported. Our mission is to deliver innovative, high-impact technology solutions that streamline processes, enhance decision making, and drive efficiency across the business. We also own the firm’s AI roadmap, integrating frontier models and capabilities where they deliver real value.

This is a hands-on, full-stack role working with Java and Python, where you'll design and develop cutting edge solutions while also empowering analysts to elevate their data science and development capabilities. You’ll collaborate with a supportive team while taking ownership of projects—from initial scoping and architecture to development and deployment—solving complex problems and driving meaningful change. If you're passionate about technology, thrive in a fast-paced, collaborative environment, and want to build software that makes a real difference, we'd love to hear from you!

Requirements:

• Strong software development skills with expertise in Java, capable of writing high-quality, well structured, well-tested code.
• A keen interest in financial markets and the trading lifecycle, with a proactive approach to learning new concepts.
• Excellent communication skills (both written and verbal), with the ability to collaborate effectively across technical and non-technical teams.

Preferred:

• Experience with Python, C#
• Hands-on experience working with relational databases, including schema design, query optimization, and performance tuning.
• Familiarity with data science principles and methodologies, with experience applying them in real-world scenarios.
• Experience with our core stack, including Hibernate, PostgreSQL, Maven, Guice, NumPy, and Pandas.
• Exposure to financial markets, either through formal education or professional experience

Miro is looking for a Machine Learning Research Engineer to serve as the technical "North Star" for our Machine Learning organization. You will operate as an Individual Contributor, driving the architectural decisions behind the "Intelligent Canvas."

Your challenge is unique in the industry: You are not just processing text. You are building models that understand spatial relationships, visual diagrams, and unstructured collaboration. You will research, prototype, and ship novel architectures that combine Large Language Models (LLMs), Computer Vision, and Graph Neural Networks (GNNs) to make Miro the smartest collaboration platform on earth.

What you’ll do

• Design, train, and ship production-grade ML models—including deep learning, NLP, and computer vision systems—that solve complex business problems and power core product features.
• Conduct deep exploratory research on massive datasets to uncover novel patterns in user behavior and content creation, translating raw data insights into new predictive modeling opportunities.
• Apply advanced fine-tuning strategies (e.g., PEFT, LoRA) to adapt state-of-the-art foundation models to specific domain tasks, rigorously experimenting to maximize performance.
• Architect scalable ML pipelines for data processing, feature engineering, training, and evaluation, ensuring high data quality and system reliability.
• Optimize model performance for latency, throughput, and resource utilization, balancing model complexity with production constraints (e.g., overfitting vs. underfitting, compute efficiency).
• Collaborate cross-functionally with data engineers, product managers, and software engineers to translate business requirements into technical ML specifications and integrate models into user-facing applications44.
• Champion MLOps excellence by automating deployment workflows, implementing CI/CD for ML, and establishing robust monitoring for model drift and health.
• Stay at the forefront of ML research, evaluating novel algorithms and techniques (e.g., Transformer architectures, quantization) to drive innovation and technical strategy.

What you’ll need

• Strong foundation in ML theory and statistics, including hypothesis testing, probability distributions, regression, classification, and optimization techniques.
• Solid engineering fundamentals. You are comfortable writing production-level Python and have a deep understanding of data structures, algorithms, and distributed system design.
• Deep proficiency in Python and the modern ML stack, with hands-on experience using libraries like Pandas, NumPy, Scikit-learn, and deep learning frameworks (PyTorch, TensorFlow).
• Gradient Debugging: Expertise in PyTorch or JAX, including experience with distributed training (e.g., DDP, FSDP) and debugging complex gradient issues.
• Applied Research: Ability to read, implement, and improve upon the latest academic papers (NeurIPS, ICML, CVPR). You don't just use libraries; you understand the math underneath them and can reproduce results in peer-reviewed papers.
• Track record of end-to-end ML delivery, from exploratory data analysis (EDA) and feature engineering to training, validation, and deploying models in a production environment.
• Experience with large-scale systems, capable of designing resilient architectures that handle vast datasets and high-throughput inference requests.
• Strong engineering mindset, valuing code quality, testing, modularity, and maintainability just as highly as model accuracy.

Education + Experience

• Option A: Bachelor's or Master's degree in Computer Science, Mathematics, Statistics, or related field plus ~3+ years of professional ML engineering experience.
• Option B: No formal degree, ~6+ years of industry experience demonstrating equivalent proficiency in building and shipping ML systems.

What's in it for you

LON:

• Competitive equity package
• Health insurance for you and your family
• Corporate pension plan
• Lunch, snacks and drinks provided in the office
• Wellbeing benefit and WFH equipment allowance
• Annual learning and development allowance to grow your skills and career
• Opportunity to work for a globally diverse team
  

Multi Location: Amsterdam / Berlin / Yerevan / London:

• Competitive equity package
• Lunch, snacks and drinks provided in the office
• Wellbeing benefit and WFH equipment allowance
• Annual learning and development allowance to grow your skills and career
• Opportunity to work for a globally diverse team

Recruiter: #LI-MH1

AI Engineer - FDE (Forward Deployed Engineer) (ALL LEVELS)

Req ID: CSQ426R186

Mission

The AI Forward Deployed Engineering (AI FDE) team is a highly specialised customer-facing AI team at Databricks. We deliver professional services engagements to help our customers build and productionize first-of-its-kind AI applications. We work cross-functionally to shape long-term strategic priorities and initiatives alongside engineering, product, and developer relations, as well as support internal subject matter expert (SME) teams. We view our team as an ensemble: we look for individuals with strong, unique specialisations to improve the overall strength of the team. This team is the right fit for you if you love working with customers, teammates, and fueling your curiosity for the latest trends in GenAI, LLMOps, and ML more broadly.

The impact you will have:

• Develop cutting-edge GenAI solutions, incorporating the latest techniques from our Mosaic AI research to solve customer problems
• Own production rollouts of consumer and internally facing GenAI applications
• Serve as a trusted technical advisor to customers across a variety of domains
• Present at conferences such as Data + AI Summit, recognized as a thought leader internally and externally
• Collaborate cross-functionally with the product and engineering teams to influence priorities and shape the product roadmap 

What we look for:

• Experience building GenAI applications, including RAG, multi-agent systems, Text2SQL, fine-tuning, etc., with tools such as HuggingFace, LangChain, and DSPy
• Expertise in deploying production-grade GenAI applications, including evaluation and optimizations 
• Extensive years of hands-on industry data science experience, leveraging common machine learning and data science tools, i.e. pandas, scikit-learn, PyTorch, etc.
• Experience building production-grade machine learning deployments on AWS, Azure, or GCP
• Graduate degree in a quantitative discipline (Computer Science, Engineering, Statistics, Operations Research, etc.) or equivalent practical experience
• Experience communicating and/or teaching technical concepts to non-technical and technical audiences alike
• Passion for collaboration, life-long learning, and driving business value through AI
• [Preferred] Experience using the Databricks Intelligence Platform and Apache Spark™ to process large-scale distributed datasets

We’re looking for a talented Research Data Scientist who expects more from their career. It’s a chance to extend and improve dunnhumby’s world class science capabilities. It’s an opportunity to work with a market-leading business to explore new opportunities for us and influence global retailers and suppliers.

Joining our team, you’ll work with world class and passionate people to apply machine learning and statistical techniques to business problems. You’ll contribute to the research and implementation of new approaches to address complex problems and perform data analysis and model validation. You’ll have the opportunity to present results to a variety of internal stakeholders and will apply these techniques and algorithms to create dunnhumby science solutions that can be delivered across our clients and engineered into science modules.

This role will be focussed across insight automation and product assortment, with applications of science including identifying new and growing product needs, optimising the mix of products, predicting the impact of changes, product attribute generation and applications of generative AI for product support and insights.

What you'll be doing:

• Create new science-based solutions that can be captured as science modules and applied across clients, with support from senior team members.
• Pick up new machine learning approaches, such as regularised regression, clustering or tree-based ensembles, graph-based approaches, natural language processing and neural network techniques and apply them on client data.
• Perform exploratory data analysis to characterise and visualise datasets 
• Extend and develop programming skills, in languages such as Python and Spark, to develop efficient science code for science modules.
• Help identify new opportunities within the Data Science space for future dunnhumby solutions.
• Implement advice from colleagues to resolve challenges.
• Follow Quality Assurance processes, ways of working and meet coding standards.
• Ensure smooth running of your projects, working with senior team members for direction.
• Build strong relationships within the team and with internal stakeholders, ensuring clear and effective communication.

Who you’ll get to work with:

• Within dunnhumby you’ll primarily work with
• Applied and Research Data Scientist teams
• Data Science Engineering teams
• Product and Client teams where required

What you'll need:

• Master’s degree or equivalent in Computer Science, Artificial Intelligence, Machine Learning, Statistics, Applied Statistics, Physics, Engineering, Biology or related field.
• Experience with machine learning techniques such as regularised regression, clustering or tree-based ensembles, and the ability to implement them through libraries.
• Experience with programming, ideally Python, and the ability to quickly pick up handling large data volumes with modern data processing tools, e.g. by using Hadoop / Spark / SQL
• Experience with or ability to quickly learn open-source software including machine learning packages, such as Pandas and scikit-learn, along with data visualisation technologies.
• A willingness to present your work to both technical and non-technical audience and to contribute to the wider data science community.

A plus if you also have:

• PhD in Computer Science, Artificial Intelligence, Machine Learning, Statistics, Applied Statistics, Physics, Engineering, Biology or related field.
• Experience in retail sector.

We’re looking for a talented Senior Research Data Scientist who expects more from their career. It’s a chance to extend and improve dunnhumby’s world class science capabilities. It’s an opportunity to work with a market-leading business to explore new opportunities for us and influence global retailers and suppliers.

Joining our team, you’ll work with world class and passionate people to apply machine learning and statistical techniques to business problems. You’ll contribute to the research and implementation of new approaches to address complex problems and perform data analysis and model validation. You’ll have the opportunity to present results to a variety of internal stakeholders and will apply these techniques and algorithms to create dunnhumby science solutions that can be delivered across our clients and engineered into science modules.

This role will be focussed across insight automation and product assortment, with applications of science including identifying new and growing product needs, optimising the mix of products, predicting the impact of changes, product attribute generation and applications of generative AI for product support and insights.

What you'll be doing:

• Create new science-based solutions that can be captured as science modules and applied across clients, with support from senior team members.
• Pick up new machine learning approaches, such as regularised regression, clustering or tree-based ensembles, graph-based approaches, natural language processing and neural network techniques and apply them on client data.
• Perform exploratory data analysis to characterise and visualise datasets 
• Extend and develop programming skills, in languages such as Python and Spark, to develop efficient science code for science modules.
• Help identify new opportunities within the Data Science space for future dunnhumby solutions.
• Implement advice from colleagues to resolve challenges.
• Follow Quality Assurance processes, ways of working and meet coding standards.
• Ensure smooth running of your projects, working with senior team members for direction.
• Build strong relationships within the team and with internal stakeholders, ensuring clear and effective communication.

Who you’ll get to work with:

• Within dunnhumby you’ll primarily work with
• Applied and Research Data Scientist teams
• Data Science Engineering teams
• Product and Client teams where required

What you'll need:

• Master’s degree or equivalent in Computer Science, Artificial Intelligence, Machine Learning, Statistics, Applied Statistics, Physics, Engineering, Biology or related field.
• Experience with machine learning techniques such as regularised regression, clustering or tree-based ensembles, and the ability to implement them through libraries.
• Experience with programming, ideally Python, and the ability to quickly pick up handling large data volumes with modern data processing tools, e.g. by using Hadoop / Spark / SQL
• Experience with or ability to quickly learn open-source software including machine learning packages, such as Pandas and scikit-learn, along with data visualisation technologies.
• A willingness to present your work to both technical and non-technical audience and to contribute to the wider data science community.

A plus if you also have:

• PhD in Computer Science, Artificial Intelligence, Machine Learning, Statistics, Applied Statistics, Physics, Engineering, Biology or related field.
• Experience in retail sector.

1721 - Associate Director, Analytics

WPP is the trusted growth partner for the world's leading brands. With exceptional talent, trusted data and intelligence, and world-class partnerships - all united by our pioneering agentic marketing platform, WPP Open - we help clients navigate change, capture opportunity, and deliver transformational growth.

WPP Media is WPP's AI-driven media operating unit, bringing together media, data, and partnerships to deliver creative personalisation at scale. Connected through WPP Open and powered by Open Intelligence, clients see exactly where, how, and why their media investment is working.

For more information, visit wppmedia.com.

About WPP Media

WPP is the creative transformation company. We use the power of creativity to build better futures for our people, planet, clients and communities. For more information, visit wpp.com.

WPP Media is WPP's global media collective. In a world where media is everywhere and in everything, we bring the best platform, people, and partners together to create limitless opportunities for growth. For more information, visit wppmedia.com

About EssenceMediacom: A Leading WPP Media Brand

EssenceMediacom is a new breed of media agency. Grounded in analytics & insights and powered by data & technology, we believe in the power of media and creative to drive breakthroughs for the world's best brands. We help clients understand the modern marketing paradox and discover the breakthroughs brands need to win with their consumers. We are designed for the new communications economy - built on data & technology, built for people & algorithms, built around diverse schools of thought, built to test & learn at scale, and, crucially, built to evolve.

Role Summary and Impact

We are seeking an Associate Director to join our Global Analytics & Insights team, reporting into the VP of Global Analytics. The team focuses on media effectiveness measurement, campaign analysis and client communication to help make brands become more valuable to the world.

You will be working with a leading travel brand, to harness their data and improve the performance of their campaigns, developing and deploying media measurement solutions. Communication with client stakeholders and effective management of assigned tasks is critical in this role. You will be joining an award winning team, with more than 16 tech and media industry awards to our name, including Campaign Magazine's Tech Awards Agency of the Year, Best Use of AI, and Breakthrough Tech as Part of a Campaign awards.

We have invested in giving you the tools to make you as successful as possible, including training/development, full access to Google Cloud Platform, an integrated AI platform leveraging common marketplace LLMs as well as access to a wider global community of analysts and data scientists.

Some of the things we'd like you to do

Partner with the Global Analytics lead to develop and communicate global measurement frameworks to local regional and market level teams

Operationalize global measurement approaches such local regions and markets approach media analytics in a consistent way

Develop standardized analytics tools and analysis through the development of AI agents

Build and apply a deep understanding of marketing objectives to support Account teams with comprehensive measurement and testing plans.

Develop deep understanding of marketing platform testing and targeting abilities, and act in a consultative capacity in their implementation to regional teams

Deliver insightful campaign reviews with actionable recommendations to improve marketing effectiveness.

Provide actionable insights and design experiments to optimise campaign performance - focusing on brand and conversion lift studies.

Be a reliable day-to-day point of contact for global clients and maintain robust client relationships.

Coordinate with third-party vendors for the assessment and management of bespoke measurement solutions, including contracts and SOWs.

Manage relationships with data engineering teams and set automation strategies to integrate new tools and solutions.

Translate complex data concepts for stakeholders and contribute to the company's data strategy, promoting data-driven innovation within the media industry.

Skills and Experience

At WPP Media, we believe in the power of our culture and our people. It's what elevates us to deliver exceptional experiences for both our clients and each other. In this role it will be critical to embrace WPP & WPP Media's shared core values:

Be Extraordinary by Leading Collectively to Inspire transformational Creativity.

Create an Open environment by Balancing People and Client Experiences by Cultivating Trust.

Lead Optimistically by Championing Growth and Development to Mobilize the Enterprise.

• You will be highly numerate: able to confidently interpret data and apply statistical tests to draw robust conclusions. Holding a degree(s) in a quantitative field: Statistics, Mathematics, Economics, Engineering, Physical Science or Computer Science
• Experience in analytics, measurement, data science, or a related field
• Knowledge of applying measurement to media campaigns through Meta/Google/TikTok/Snapchat/Pinterest, through brand and conversion lift studies, matched market tests or otherwise
• Well developed problem-solving skills and the ability to think critically and creatively
• Strong understanding of statistics including hypothesis testing, descriptive statistics and distribution theory
• Strong communication skills, with the ability to present complex ideas to both technical and non-technical audiences
• Able to work independently and as part of a cross-functional team, using project management tools such as Asana/Wrike. Ability to project manage analytics projects.
• Highly capable at presenting data in a visually engaging and insightful manner that cuts through the noise
• Experience in mentorship and management, ability to display empathy in difficult situations and lead by example
• Stay up-to-date with the latest industry trends and advancements in data science and analytics
• Proficiency in SQL & R/Python, including understanding of packages such as pandas, numpy, scipy & matplotlib is desired
• Strong understanding of what data points can be collected and analysed in across media analytics campaigns, and how each data point should be analysed. Including knowledge of media data and incremental measurement, including both Direct Response and Brand campaigns

Nice to haves:

• Experience with digital ad technologies (SA360, GA, Campaign Manager, DV360, Meta Business Manager), site analytics and tools
• Experience with cloud technologies, such as GCP
• Proven understanding and experience with digital ad platforms APIs
• Knowledge of market research methodologies
• Speaking any European languages

Life at WPP Media & Benefits

Our passion for shaping the next era of media is powered by our commitment to Be Extraordinary, investing in our employees to inspire transformational creativity. We also Lead Optimistically, firmly believing in and Championing Growth and Development for every individual. This commitment allows WPP Media employees to leverage the extensive global WPP Media & WPP networks to pursue their passions, build vital professional connections, and learn at the cutting edge of marketing and advertising. 

We Create an Open environment built on trust and respect, where everyone feels they belong and has opportunities to progress. This inclusive culture is fostered through a variety of employee resource groups and frequent in-office events showcasing team wins, sharing thought leadership, and celebrating holidays and milestone events. Our comprehensive benefits package reflects this commitment, including competitive medical, group retirement plans, vision, and dental insurance, significant paid time off, preferential partner discounts, and employee mental health awareness days. 

WPP Media is an equal opportunity employer and considers applicants for all positions without discrimination or regard to characteristics. We believe the best work happens when we're together, fostering creativity, collaboration, and connection in this open and supportive environment. That's why we’ve adopted a hybrid approach, with teams in the office around four days a week. If you require accommodations or flexibility, please discuss this with the hiring team during the interview process. 

Please note this is a UK based role and requires individuals to have the right to work in this location

Please read our Privacy Notice (https://www.wppmedia.com/pages/privacy-policy) for more information on how we process the information you provide.

While we appreciate all applications received, only those candidates selected for an interview will be contacted. 

#LI-Promoted

A Career in Long/Short Equities at Point72 

Long/Short Equity is Point72’s core investment strategy, and its success depends upon our sector-based investing teams comprised of portfolio managers and research analysts. As an ever-increasing amount of data is applied to the fundamental equity strategies, we are seeking a dedicated data engineer intern to help design and build solutions that enable investment professionals to extract insights from large, complex, Compliance-approved structured and unstructured data sets.  
 
Over your 10-week internship in our London office, you will gain exposure to a variety of activities, which may include: 

• Developing and supporting data processing pipelines including but not limited to ingestion, transformation, and end-customer delivery 

• Working closely with investment professionals, researchers, and data scientists to design, build, launch, and maintain robust end-to-end data pipelines and tools that help extract the most value out of our data assets 

• Building out cloud-based infrastructure using distributed techniques for other data engineers, data scientists, and researchers 

• Creating and supporting visualisation and exploration capabilities around our big data sets

What Excites You 

• Transforming large unstructured data sets into valuable investment research inputs 

• Applying quantitative methods to deliver key insights 

• Learning and working with industry-leading cloud-computing technologies 

• Working as part of a cross-functional team of technologists, investment professionals, and researchers in close partnership with Compliance  

 What Excites Us 

• Great communicators who are approachable and responsive 

• Excellent attention to detail, organisation, and task management  

• An aptitude for solving complex problems 

• Strong team players who collaborate with ease, take accountability, and contribute to a thriving firm culture  

• People who take ownership, are proactive, and get the job done  

Summer Internship Program at Point72 

In addition to the learning and development you’ll receive in your day-to-day role with your team, as a part of our summer internship program you will: 

• Receive close mentorship from investing and technical professionals 

• Attend sessions with senior leaders discussing their expertise and career paths 

• Get hands-on access to the wealth of tools and resources that Point72 employees use every day 

• Gain exposure to groups and functions with unique responsibilities and perspectives on our industry 

• Develop technical, writing, and presentation skills 

 What's required 

• Pursuit of a bachelor’s or master’s degree in a quantitative discipline (computer science, maths, engineering), with an expected graduation date of Spring 2027 or later 

• Strong proficiency in SQL and Python (with an emphasis on Pandas, PySpark, etc.) 

• Excel skills and visualisation skills are preferred 

• Excellent attention to detail, organisation, and project management skills 

• Strong verbal and written communication skills 

• Commitment to the highest ethical standards  

About Point72 

Point72 is a leading global alternative investment firm led by Steven A. Cohen. Building on more than 30 years of investing experience, Point72 seeks to deliver superior returns for its investors through fundamental and systematic investing strategies across asset classes and geographies. We aim to attract and retain the industry’s brightest talent by cultivating an investor-led culture and committing to our people’s long-term growth. For more information, visit www.Point72.com/about.  

ABOUT CUBIST

Cubist Systematic Strategies, an affiliate of Point72, deploys systematic, computer-driven trading strategies across multiple liquid asset classes, including equities, futures and foreign exchange. The core of our effort is rigorous research into a wide range of market anomalies, fueled by our unparalleled access to a wide range of publicly available data sources.

ROLE/RESPONSIBILITIES

• Perform rigorous and innovative research to discover systematic anomalies in global macro markets (futures, FX, etc.)
• Perform feature engineering with price-volume, order book and alternative data at intraday to daily horizons in mid frequency trading space
• Perform feature combination and monetization using various modeling techniques
• Manage the research pipeline end-to-end, including signal idea generation, data processing, modeling, strategy backtesting, and production implementation
• Maintain and improve portfolio trading in a production environment
• Contribute to the analysis framework for scalable research

REQUIREMENTS

• Background in mathematics, statistics, machine learning, computer science, engineering, quantitative finance, or economics
• 2-6 years of signal research experience in macro trading as part of a trading team
• Specialization in swaps, fixed income, or commodities trading a plus.
• Prior professional experience with feature engineering, modeling, or monetization
• Ability to efficiently format and manipulate large, raw data sources
• Demonstrated proficiency in Python, R, or C/C++. Familiarly with data science toolkits, such as scikit-learn, Pandas
• Strong command of foundations of applied and theoretical statistics, linear algebra, and machine learning techniques
• Collaborative mindset with strong independent research abilities
• Commitment to the highest ethical standards

Research Scientist (Machine Learning), London

Your impact 

As a Research Scientist in machine learning (ML), you will play an exciting role in building greenfield machine learning based models and algorithms that will power our platform to transform the drug discovery world as we know it. 

Working in a highly creative, fast-paced and interdisciplinary environment, you will be partnering with leading engineers and scientists to conceive, design, and develop cutting edge machine learning algorithms to unlock new modelling and predictive power which will be critical to the organisation’s success. You will draw upon your existing deep research experience whilst learning from those around you, to apply novel techniques and ideas to newly encountered computational biology and chemistry problems.

Depending on your experience:

You will create and lead projects, bringing together a variety of disciplined scientists and engineers to pursue some of the most ambitious modelling problems with deep learning - as well as providing technical mentorship and people management for others in the ML community at Isomorphic Labs

You will be instrumental in leading greenfield machine learning based research projects, building the models, and algorithms that will power our platform to transform the drug discovery world as we know it.

What you will do

• Contribute to our research directions in machine learning by using your extensive knowledge of the field to apply world-leading ML algorithms to drug discovery.
• Identify and create novel ML techniques and the required data to train.
• Develop the architectures and training algorithms of machine learning models.
• Analyse and tune experimental results to inform future experimental directions.
• Implement and scale training and inference engineering frameworks.
• Report and present research findings and developments clearly and efficiently, to both other ML scientists and scientists of different disciplines.
• Iterate collaboratively with scientists and domain experts, sharing your own domain experience.
• Suggest and engage in team collaborations to meet ambitious research goals.
  
  Depending on your experience:
• Provide technical mentorship and guidance to the ML research community, advising on projects, and shaping our research roadmap based on your deep technical expertise.
• Provide developmental support to other ML research scientists.
• Create, lead, and run ML research projects, fostering collaborative and diverse teams to solve high priority modelling problems.Cultivate a diverse and inclusive research culture.

Skills and qualifications 

Essential

• PhD or equivalent practical experience in a technical field.
• A proven track record in machine learning using deep learning techniques, including designing new architectures, hands-on experimentation, analysis, and visualisation.
• Strong knowledge of linear algebra, calculus and statistics.
• Experience using ML frameworks such as JAX, PyTorch, or TensorFlow, and scientific software such as NumPy, SciPy, or Pandas.
• A passion for applying ML research to real world problems.
• Depending on your experience: project supervision, leadership, or management.

Nice to have

• PhD in machine learning or computer science.
• Relevant research experience to the position such as post doctoral roles, a proven track record of publications, or contributions to machine learning codebases.
• Experience working in a scientific environment across disciplines (particularly biology, chemistry, physics).
• Experience working with biological or chemical data and biological or chemistry software.
• Experience working with real-world datasets.
• Experience with ML on accelerators.
• Experience in any of: large scale deep learning, generative models, graph neural networks, deep learning for drug discovery, deep learning for computer vision, 3D graphics/robotics, real-world applied RL.

Research Scientist - Applied Large Language Models 

Your impact 

As a Research Scientist focused on the application of Large Language Models (LLMs), you will play an exciting role in bringing cutting edge technologies to bear across our research areas to transform the drug discovery world as we know it. 

Working in a highly creative, fast-paced and interdisciplinary environment, you will be partnering with leading research scientists and engineers to conceive, design, and develop cutting edge LLM applications that help to unlock new modelling capabilities and predictive power which will be critical to the organisation’s success. You will draw upon your existing deep understanding and experience whilst learning from those around you, to apply novel techniques and ideas to newly encountered computational biology and chemistry problems.

Depending on your experience:

You will both partner with teams across our existing research areas and create and lead standalone projects, bringing together a variety of disciplined scientists and engineers to pursue some of the most ambitious modelling problems through the application of LLMs - as well as providing technical mentorship and people management for others in the ML community at Isomorphic Labs.

You will be instrumental in leading machine learning based research projects, building the models, and algorithms that will power our platform to drive us close to achieving our ambitious mission to one day solve all disease with the help of AI.

What you will do

• Contribute to core research in machine learning by pushing the boundaries of Large Language Models in their application to the world of drug discovery
• Develop and refine LLM-driven approaches for multiple use cases across our research areas, using your extensive knowledge of the field to modify and apply models and explore their capabilities when applied to complex biological and medical challenges.
• Identify and create novel ML techniques and the required data to train and apply models
• Analyse and tune experimental results to inform future experimental directions.
• Implement and scale training and inference engineering frameworks
• Report and present research findings and developments clearly and efficiently, to both other ML scientists and scientists of different disciplines
• Iterate collaboratively with scientists and domain experts, sharing your own domain experience
• Suggest and engage in team collaborations to meet ambitious research goals
  
  Depending on your experience:
• Provide technical mentorship and guidance to the ML research community, advising on projects, and shaping our research roadmap based on your deep technical expertise.
• Provide developmental support to other ML research scientists.
• Create, lead, and run ML research projects, fostering collaborative and diverse teams to solve high priority modelling problems. Cultivate a diverse and inclusive research culture.

Skills and qualifications 

Essential

• PhD or equivalent practical experience in a technical field
• Highly specialized LLM builder with a passion for, and strong experience in, applying LLMs to novel problem spaces
• Deep understanding and experience of model architectures, training methods, and techniques for application of LLMs, including deployment for bespoke use cases and applications, established experience in post-training, reasoning, test-time scaling, tool-use, alignment, agents, LLM research, as well as reinforcement learning and fine-tuning 
• Strong knowledge of linear algebra, calculus and statistics.
• Experience using ML frameworks such as JAX, PyTorch, or TensorFlow, and scientific software such as NumPy, SciPy, or Pandas.
• Depending on your experience: project supervision, leadership, or management.
• Strong knowledge of LLM landscape today, and likely developments for the near future
• Experience working with real-world datasets.

Nice to have

• PhD in machine learning or computer science.
• Relevant research experience to the position such as post doctoral roles, a proven track record of publications, or contributions to machine learning codebases.
• A strong background in biology or medicine, enabling you to bridge the gap between advanced AI capabilities and complex scientific problems in drug discovery
• Experience working in a scientific environment across disciplines (particularly biology, chemistry, physics), and with real world biological or chemical datasets and biological or chemistry software
• Experience in computational chemistry, bioinformatics, or related fields would be highly beneficial, along with a track record of applying AI to real-world scientific challenges
• Experience with multi-parameter optimization
• Experience in any of: large scale deep learning, generative models, graph neural networks, deep learning for drug discovery, deep learning for computer vision, 3D graphics/robotics, real-world applied RL

Research Scientist (Machine Learning), Lausanne

Your impact 

As a Research Scientist in machine learning (ML), you will play an exciting role in building greenfield machine learning based models and algorithms that will power our platform to transform the drug discovery world as we know it. 

Working in a highly creative, fast-paced and interdisciplinary environment, you will be partnering with leading engineers and scientists to conceive, design, and develop cutting edge machine learning algorithms to unlock new modelling and predictive power which will be critical to the organisation’s success. You will draw upon your existing deep research experience whilst learning from those around you, to apply novel techniques and ideas to newly encountered computational biology and chemistry problems.

Depending on your experience:

You will create and lead projects, bringing together a variety of disciplined scientists and engineers to pursue some of the most ambitious modelling problems with deep learning - as well as providing technical mentorship and people management for others in the ML community at Isomorphic Labs

You will be instrumental in leading greenfield machine learning based research projects, building the models, and algorithms that will power our platform to transform the drug discovery world as we know it.

What you will do

• Contribute to our research directions in machine learning by using your extensive knowledge of the field to apply world-leading ML algorithms to drug discovery.
• Identify and create novel ML techniques and the required data to train.
• Develop the architectures and training algorithms of machine learning models.
• Analyse and tune experimental results to inform future experimental directions.
• Implement and scale training and inference engineering frameworks.
• Report and present research findings and developments clearly and efficiently, to both other ML scientists and scientists of different disciplines.
• Iterate collaboratively with scientists and domain experts, sharing your own domain experience.
• Suggest and engage in team collaborations to meet ambitious research goals.
  
  Depending on your experience:
• Provide technical mentorship and guidance to the ML research community, advising on projects, and shaping our research roadmap based on your deep technical expertise.
• Provide developmental support to other ML research scientists.
• Create, lead, and run ML research projects, fostering collaborative and diverse teams to solve high priority modelling problems.Cultivate a diverse and inclusive research culture.

Skills and qualifications 

Essential

• PhD or equivalent practical experience in a technical field.
• A proven track record in machine learning using deep learning techniques, including designing new architectures, hands-on experimentation, analysis, and visualisation.
• Strong knowledge of linear algebra, calculus and statistics.
• Experience using ML frameworks such as JAX, PyTorch, or TensorFlow, and scientific software such as NumPy, SciPy, or Pandas.
• A passion for applying ML research to real world problems.
• Depending on your experience: project supervision, leadership, or management.

Nice to have

• PhD in machine learning or computer science.
• Relevant research experience to the position such as post doctoral roles, a proven track record of publications, or contributions to machine learning codebases.
• Experience working in a scientific environment across disciplines (particularly biology, chemistry, physics).
• Experience working with biological or chemical data and biological or chemistry software.
• Experience working with real-world datasets.
• Experience with ML on accelerators.
• Experience in any of: large scale deep learning, generative models, graph neural networks, deep learning for drug discovery, deep learning for computer vision, 3D graphics/robotics, real-world applied RL.

1211 - Director, Data Science - DTA

About WPP Media

WPP is the creative transformation company. We use the power of creativity to build better futures for our people, planet, clients and communities. For more information, visit wpp.com.

WPP Media is WPP’s global media collective. In a world where media is everywhere and in everything, we bring the best platform, people, and partners together to create limitless opportunities for growth. For more information, visit wppmedia.com

About Choreograph: A Leading WPP Media Brand

Choreograph is WPP’s global data products and technology company. We’re on a mission to transform marketing by building the fastest, most connected data platform that bridges marketing strategy to scaled activation.

We work with agencies and clients to transform the value of data by bringing together technology, data and analytics capabilities. We deliver this through the Open Media Studio, an AI-enabled media and data platform for the next era of advertising.

We’re endlessly curious. Our team of thinkers, builders, creators and problem solvers are over 1,000 strong, across 20 markets around the world.

Role Summary and Impact

The Data Science Director, plays a critical leadership role as part of a broader team in the deployment and development of predictive models for our customers. You will lead and mentor a team, working collaboratively with senior Google Cloud and Google Marketing experts to apply advanced modeling techniques to enhance our customers' media/marketing solutions. As Team Lead you will be responsible for guiding the team in building out industry-relevant predictive models that can be applied to optimize our customers' media investments.

The role focuses on leading the application of analytical solutions based on machine learning & statistical predictive algorithms on top of the Google technology stack and agent development for our customers. We are looking for a Team Lead with significant experience in algorithmic data analysis, proven scientific research skills, and a track record of leading successful data science initiatives.

Skills and Experience

At WPP Media, we believe in the power of our culture and our people. It’s what elevates us to deliver exceptional experiences for both our clients and each other. In this role it will be critical to embrace WPP & WPP Media’s shared core values:

• Be Extraordinary by Leading Collectively to Inspire transformational Creativity.
• Create an Open environment by Balancing People and Client Experiences by Cultivating Trust.
• Lead Optimistically by Championing Growth and Development to Mobilize the Enterprise.

This is an excellent opportunity for a Team Lead, to join the Data and Technology Consulting Team. You will be instrumental in strategising how to tackle and take apart large and messy datasets of structured and unstructured data, oversee the building and implementation of models and algorithms, agents and design and run experiments to optimise clients customer insights, analytics and customer experience. The ideal candidate will have a love of getting their hands dirty, while also empowering and developing their team to do the same.

RESPONSIBILITIES:

• Lead the team in the creation, management, and continuous improvement of AI/ML and models and agents used to measure, optimize, and activate business transformation, including creative, media campaigns and broader marketing objectives.
• Drive the development and deployment of industry-relevant strategies and solutions.
• Ensure comprehensive documentation of data science projects, establishing best practices for replicable and scalable analytical processes across clients.
• Guide the team in building out compelling content for presentations to demonstrate the performance and value of statistical and predictive models.
• Oversee the delivery of robust mathematical analysis, ensuring accuracy and strategic relevance.
• Accountable for the team's production of high-standard campaign reports, studies, presentations, and proposals.
• Achieve continuous improvement by proactively assessing Choreograph's working relationships, practices, and methods, and implementing enhancements.
• Lead the establishment and optimization of MLOps processes leveraging the GCP toolset.
• Drive and demonstrate measurable success and impact for clients and the team.

REQUIREMENTS:

• Hands-on experience with building out machine learning models with Python, in a leadership or senior mentorship role.
• Advanced education and background in machine learning, computer science, physics, applied mathematics, or statistics.
• Expert-level hands-on experience in developing complex query structures with SQL and/or NoSQL query languages, and experience guiding others.
• Expert-level hands-on experience working with GCP’s AI Capabilities, including leveraging BigQuery ML, Vertex AI, and other relevant services.
• Extensive hands-on experience with a broad range of machine learning techniques using (TensorFlow, Keras, PyTorch, Scikit-learn, XGBoost, Pandas, NLTK, Spark MLib).
• Deep experience and understanding of deep learning techniques (TensorFlow, Theano, MXNet).
• Proven understanding and experience in software engineering best practices, DevOps, and MLOps, with a track record of implementing or leading these initiatives.
• Solid grounding in applied mathematics, especially optimization and graph theory, and advanced statistics.
• Significant commercial or academic experience in leading the development and deployment of complex ML & AI solutions using Python/R.
• In-depth knowledge of machine learning algorithms and their practical applications.
• Advantageous to have extensive experience in Google Marketing Platform and the use of Ads Data Hub.
• Exceptional capabilities in the areas of data engineering, data modeling, and complex big data analysis, with experience leading teams in these domains.
• Strong business analysis skills and deep understanding of analytics, with the ability to translate complex data into strategic business value.
• Exceptional communication and presentation skills, capable of influencing stakeholders at all levels.
• Passionate about working in an extremely fast-paced, demanding, and fluid environment, with a desire to build and lead a high-performing team and contribute significantly to a growing company.

Life at WPP Media & Benefits

Our passion for shaping the next era of media includes investing in our employees to help them do their best work, and we’re just as committed to employee growth as we are to responsible media investment. WPP Media employees can tap into the global WPP Media & WPP networks to pursue their passions, grow their networks, and learn at the cutting edge of marketing and advertising. We have a variety of employee resource groups and host frequent in-office events showcasing team wins, sharing thought leadership, and celebrating holidays and milestone events. Our benefits include competitive medical, group retirement plans, vision, and dental insurance, significant paid time off, preferential partner discounts, and employee mental health awareness days.  

WPP Media is an equal opportunity employer and considers applicants for all positions without discrimination or regard to particular characteristics. We are committed to fostering a culture of respect in which everyone feels they belong and has the same opportunities to progress in their careers.

We believe the best work happens when we're together, fostering creativity, collaboration, and connection. That's why we’ve adopted a hybrid approach, with teams in the office around four days a week. If you require accommodations or flexibility, please discuss this with the hiring team during the interview process.

Please note this is a UK based role and requires individuals to have the right to work in this location

Please read our Privacy Notice (https://www.wppmedia.com/pages/privacy-policy) for more information on how we process the information you provide.

#LI-Promoted

About the Role:

We are growing the Data Team at iSAM. This is a full stack python development role, focused on data. An ideal candidate would have enthusiasm for quantitative data and a drive to understand, model and analyse a variety of datasets, collaborating across a fast paced, multi-disciplinary team.

Responsibilities:

• Onboard, build and model datasets of varying frequency
• Explore data, conduct analysis and integrate data into our backtest framework
• Collaborate closely with quantitative researchers and the wider investment teams
• Production support for datasets in live trading
• Ongoing work to grow and develop the system across strategies and regions

Qualifications:

• 3+ years of commercial software engineering experience
• Strong python programming skills
• Experience with financial data, ideally equities, derivatives or other tradeable asset classes
• Experience working with data in quantitative investing and the ability to deliver practical solutions in imperfect data environments
• Familiarity with numerical python libraries e.g., numpy, pandas and polars
• SQL experience with any flavour of SQL
• Experience with version control, test driven development, linux and navigating and working in large codebase
• Flexibility to work across a variety of areas in a highly collaborative team and take significant ownership of tasks

As a Technical Solutions Engineer II at Diligent, you will play a critical role in supporting complex and enterprise pre-sales engagements by designing, prototyping, and demonstrating tailored GRC solutions. You will partner closely with Sales, Solution Architects, Product, and Professional Services to translate sophisticated customer requirements into compelling technical solutions that accelerate deal velocity and drive technical wins.

This role is ideal for someone who enjoys hands-on technical work, customer-facing problem solving, and building prototypes and automations that showcase how modern GRC platforms integrate into enterprise ecosystems.

Key Responsibilities

Pre-Sales Technical Execution

• Partner with Sales, SEs, and Solution Architects to support mid-market and enterprise GRC opportunities
• Own the technical pre-sales win for assigned deals, including solution validation, design, and risk mitigation
• Design and deliver tailored demos, technical deep dives, and proof-of-concepts (POCs)

Solution Prototyping & Automation

• Build demo prototypes, automation scripts, and integration examples using Python
• Develop solutions and workflows to demonstrate:
  • Data ingestion and transformation
  • API-based integrations
  • Process automation and orchestration
• Leverage REST APIs to integrate Diligent with third-party enterprise systems

Technical Storytelling

• Translate complex GRC use cases into clear, value-driven technical narratives
• Prepare demo assets, technical diagrams, and supporting materials for customer engagements
• Confidently present to technical, business, and executive stakeholders

Cross-Functional Collaboration

• Work closely with Product Management to:
  • Stay current on new capabilities and roadmap
  • Provide structured feedback from customer engagements
• Collaborate with Marketing on webinars, conferences, and thought-leadership initiatives
• Support internal enablement by sharing reusable demo assets and technical patterns

Required Experience/Skills

Technical Background

• 3+ years of experience in:
  • Pre-sales engineering
  • Technical consulting
  • Solutions architecture
  • Software implementation or integration roles
• Strong proficiency in Python, including experience with:
  • REST APIs
  • Data handling and transformation
  • Automation scripts and tooling
• Familiarity with common Python libraries (e.g., Pandas, Requests)
• Exposure to:
  • Workflow automation platforms
  • Data pipelines or ETL processes
  • Security, audit, or compliance tooling
• Experience building demo environments or reusable technical accelerators

Enterprise & Customer-Facing Experience

• Experience supporting enterprise or regulated customers
• Experience working in customer-facing roles within B2B SaaS or enterprise software
• Comfortable engaging with senior stakeholders and complex buying committees
• Proven ability to balance technical depth with business value articulation

Domain & Mindset

• Strong interest in Governance, Risk, Compliance, Audit, or Data Analytics
• Experience with GRC platforms, regulated industries, or enterprise data workflows is a strong plus
• Curious, proactive, and comfortable operating in fast-moving environments

Maven is a market-leading proprietary trading firm deploying its own capital across discretionary, systematic, and market-making strategies. Backed by deep expertise in trading, technology, and research, we are relentlessly focused on improving liquidity across global listed derivatives. Through advanced execution and pricing technologies, we improve how financial markets operate.

Responsibilities:

• Develop Advanced Analytics Infrastructure: Engineer scalable Python-based libraries and tools that standardize performance metrics across the group. create automated workflows that convert raw trading data into high-value insights for Portfolio Managers and the Investment Committee.
• Conduct Quantitative Strategy Research: Perform rigorous statistical analysis on trade and portfolio-level data to decompose PnL drivers. Identify alpha decay, parameter inefficiencies, and execution drag to deliver actionable research that directly improves performance.
• Improve Returns on Existing Strategies: Analyze performance on a trade and strategy level to identify inefficiencies of optimisation areas. Deliver recommendations backed by data and maintain follow through. 
• Highlight Trading Risks & Opportunities: monitor portfolio exposures, performance trends, and market signals to highlight emerging risks and identify underutilized or mispriced opportunities across various strategies.
• Support Strategy Development: support the PM onboarding process, and business development initiatives into new product groups and strategies. 

Candidate Specifications:

• At least 2–5 years of experience specifically within a Hedge Fund, Proprietary Trading Firm, or Quantitative Asset Manager.
• Strong proficiency in Python (Pandas, NumPy, SciPy) for data analysis and simulation; SQL knowledge is essential.
• Deep understanding of the trade lifecycle and buy-side strategies (e.g., Relative Value, Stat Arb, Volatility).
• Excellent communication and teamwork skills
• Ability to demonstrate wider interest in financial markets
• Outstanding numerical skills
• Proactive interest in improving existing trading strategies and identifying new opportunities
• Ability to take a high level of responsibility in an expanding, highly successful firm
• Excellent attention to detail
• Fast problem-solving skills

What We Offer:

• A great environment whereby technology is key to our success
• The upside of a start-up without the associated risks
• Friendly, informal and highly rewarding culture
• A fast-growing global firm with plenty of opportunities where you will have a significant impact

About the Role:

iSAM is offering Quantitative Research Internship opportunities for PhD students in their penultimate year of study in a quantitative discipline. These internships will take place during Summer 2026 and will run for 12 weeks.

Roles are available across three key areas of the business:

• Quantitative Trading within iSAM Securities
• Quantitative Research within the iSAM Options desk
• Quantitative Research within iSAM Funds

iSAM is an innovative financial technology firm specialising in systematic and quantitative trading. No prior industry experience is required—only intellectual curiosity, strong analytical ability, and a genuine eagerness to learn.

As an intern, you will be fully embedded within your team and contribute meaningfully to live research and trading initiatives. The role is research-focused and involves applying advanced statistical and mathematical techniques to develop and evaluate quantitative signals and strategies.

Responsibilities:

You will work as part of a collaborative research team, tackling complex and intellectually challenging problems. Responsibilities may include:

• Assisting in the research and development of systematic investment strategies across multiple asset classes
• Analysing large and complex financial datasets to identify signals, patterns, and risk characteristics
• Designing, implementing, and testing quantitative models using Python and relevant numerical and statistical libraries
• Supporting the backtesting, performance analysis, and validation of trading strategies
• Helping to maintain and enhance research infrastructure, tools, and data pipelines
• Clearly documenting research methodologies and results, and presenting findings to senior researchers
• Collaborating closely with portfolio managers, quantitative researchers, and technologists
• Investigating enhancements to existing strategies, including improvements to risk management and execution assumptions

Qualifications

• PhD student in a quantitative field (e.g. Mathematics, Physics, Statistics, Computer Science), with expected completion in 2026 or 2027
• Strong foundation in statistics and probability theory, with familiarity with machine learning techniques
• Strong programming skills in Python (experience with libraries such as NumPy, Pandas, or similar is desirable)
• Experience working in a research-driven environment, including handling large datasets and developing algorithmic solutions to complex problems
• A strong interest in financial markets and systematic trading (prior finance experience is not required)

Personal Attributes

• Highly analytical, with a strong sense of ownership and accountability
• Enjoys tackling complex problems and working through challenging mathematical or statistical questions
• Collaborative and able to work effectively with researchers, technologists, and trading teams
• Clear and concise communicator, both verbally and in writing
• Comfortable working independently while knowing when to seek input from others

Key Objectives

By the end of the internship, a successful candidate will have:

• Developed a strong understanding of how quantitative research is conducted within a live trading environment
• Contributed tangible research outputs that inform or enhance existing trading strategies or research directions
• Demonstrated the ability to translate complex mathematical and statistical ideas into robust, well-tested code
• Gained hands-on experience working with large-scale financial data and research infrastructure
• Built an understanding of the full research lifecycle, from idea generation and data analysis through to validation and presentation
• Established effective working relationships within their team, contributing proactively and collaboratively to shared objectives
• Strengthened problem-solving, communication, and technical skills in a fast-paced, intellectually rigorous setting

• Collaborate with quantitative researchers to understand their workflow, challenges, and requirements, and provide technical solutions to improve their research productivity
• Design, develop, and maintain software tools, platforms, and frameworks that enhance the efficiency and effectiveness of research activities, including data gathering, preprocessing, analysis, and model development
• Identify and implement advanced data processing techniques, algorithms, and statistical methods to optimize research workflows and enhance data analysis capabilities
• Leverage your expertise in software engineering, data engineering, and machine learning to build scalable and robust systems that facilitate large-scale data analysis and experimentation
• Conduct code reviews, provide technical guidance, and mentor junior research engineers to ensure code quality, maintainability, and adherence to best practices
• Collaborate with cross-functional teams, including quantitative researchers, data scientists, and engineering professionals, to integrate research tools and systems into the existing infrastructure
• Assist in the evaluation and implementation of third-party tools, libraries, and data sources that can enhance the research process
• Participate in research discussions, contribute ideas, and provide technical expertise to improve research methodologies and strategies
• Contribute to the development and maintenance of documentation, user guides, and training materials related to research tools and processes

• 4+ years experience working in close partnership with quantitative researchers to develop, deploy and maintain quantitatively-driven alpha strategies. Previous experience at a quantitative hedge fund is strongly preferred. 
• Masters or Ph.D. in Computer Science, Engineering, Data Science, or a related field
• Exceptional Python programming skills, with a focus on building scalable and efficient systems
• Experience with graph (DAG) representation, analysis, and processing using tools like NetworkX
• Experience with open source distributed computing tools in Python, such as Dask or Ray
• Proficiency in data processing, analysis, and visualization leveraging best-in-class open source tools, libraries, and frameworks (e.g., Pandas, Plotly, SciPy) 
• Solid understanding of statistical modeling, machine learning techniques, and their practical applications in quantitative research
• Solid understanding of the differences between L1, L2 and L3 market tick data
• Experience with AWS, Linux and Docker
• Excellent problem-solving skills and the ability to design practical solutions to complex research challenges
• Strong communication and collaboration skills to effectively work with cross-functional teams and translate research requirements into technical solutions
• Experience in recruiting, mentoring, and guiding junior team members is preferred
• Ability to travel periodically between our offices in London, NYC, and Zug, Switzerland

Are you keen to work in a well-resourced startup environment, where your ideas, experience, and drive to find creative solutions makes a difference? We’d like to hear from you.

The base salary for this role is anticipated to be between $150,000 and $225,000. This anticipated base salary range is based on information as of the time this post was created. This role may also be eligible for additional forms of compensation and benefits, such as a discretionary bonus, health, dental and other benefits plans. Actual compensation will be carefully determined based on a number of candidate factors, including their skills, qualifications and experience.

Your key skills and capabilities: 

• Gathering and documenting business and project requirements 

• Managing stakeholders of differing levels 

• Analysing and profiling large and complex datasets 

• Managing a team backlog using tools like Jira or Azure DevOps 

• Agile ways of working 

• Familiar with Online Transaction Processing (OLTP) and Online Analytical Processing (OLAP) systems 

• Creating conceptual, logical and physical data models  

• Creating mapping specifications for data migrations 

• Coordinating User Acceptance Testing (UAT) with business stakeholders 

• Excellent SQL skills 

• Knowledge of python (pandas) 

• Experience with Cloud platforms 

• Creating data dashboards using Tableau, PowerBI or Qlik and story telling 

We expect you to work closely with business to understand their current data problems, pain points and to know how to analyse and cleanse their data. Also, we expect you to design data storage solutions and be a good communicator with your technical team.