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 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.

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.

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 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 looking for a Senior Software Engineer to focus on our Treasury Infrastructure. Coders at HRT work on small, highly productive, and efficient teams that design, improve, and maintain the technology that powers worldwide trading — at HRT, the code you write is our business. You’ll have an opportunity to work closely with Treasury Quantitative Researchers and our Funding Team to design and develop HRT's Treasury Optimization and Research Platform.

We are looking for highly skilled programmers who love to code and solve complex problems, appreciate a culture of collaboration, and thrive in a performance-driven environment. You can always expect to be challenged by the ever-changing financial markets, and find yourself working on critical software in an extremely fast-paced, real-time environment.

Responsibilities

• Contribute to the engineering design and development of HRT’s Treasury Optimization Platform.
• Collaborate with Treasury Researchers on HRT’s Treasury Research Infrastructure.
• Collaborate with Quantitative Developers as well as our Funding and Finance teams on managing cash and collateral requirements.

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.
• Working experience in Python and good CS fundamentals.
• Proficiency with numerical computing libraries (Numpy, PyTorch, TensorFlow) is a plus.
• Knowledge of global portfolio financing and funding is a plus.
• Strong problem-solving skills and ability to work in a fast-paced environment.
• Excellent communication skills and ability to collaborate with engineers, researchers, and non-technical teams.

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.

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).

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.

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

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…

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 

• 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.
• Contribute towards Research group strategy and culture.
  • Identify research areas that would be valuable to the company and champion their development, ordering wrt other research objectives.
  • 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.
• The below activities in particular.
  • 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.
  • 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.

What you bring to the table

• Ability to scope and effectively deliver projects.
• Enthusiasm about using machine learning, especially deep learning and/or probabilistic methods, for science and engineering.
• 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.).
• Ideally, >4 years of experience in a data-driven role in a professional industry setting, where you have been instrumental in:
  • building machine learning models and pipelines in Python, using common libraries and frameworks (PyTorch / CUDA, ideally with exposure to JAX, NumPy / SciPy), 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…

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

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

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.

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), 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.

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

At Google DeepMind, we value diversity of experience, knowledge, backgrounds and perspectives and harness these qualities to create extraordinary impact. We are committed to equal employment opportunity regardless of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, pregnancy, or related condition (including breastfeeding) or any other basis as protected by applicable law. If you have a disability or additional need that requires accommodation, please do not hesitate to let us know.

Snapshot

We’re looking for engineers and scientists to help accelerate our research in Artificial Intelligence as part of our mission to create the next generation of Generative AI technologies. Our team has a unique mandate: to work on speculative, longer-horizon research projects that, if successful, yield step-change improvements in the capabilities of our frontier models. We target paradigm-shifting ideas and are prepared to invest the time and resources necessary to achieve them. Our goal is to ideate, research, develop, validate, and integrate these improvements into major Google technologies.

Our primary research focus is Gemini Diffusion, our state-of-the-art text diffusion model. We believe that text diffusion has the potential to unlock a new paradigm in generative AI, offering unprecedented capabilities and lightning-fast latency. With strong backing from GDM leadership, our team is dedicated to thoroughly exploring and advancing this technology.

Our team is a multi-disciplinary group of engineers and scientists that work in close collaboration, leveraging our unique skills with a strong focus on building and shipping ground-breaking AI. We are a problem-focused team, meaning we are interested in any tool or idea that can solve a concrete problem, rather than being tied to a particular set of tools.

About us

Artificial Intelligence could be one of humanity’s most useful inventions. At Google DeepMind, we’re a team of scientists, engineers, machine learning experts and more, working together to advance the state of the art in artificial intelligence. We use our technologies for widespread public benefit and scientific discovery, and collaborate with others on critical challenges, ensuring safety and ethics are the highest priority.

The role

We are looking for a Research Scientist to join our team in London and help us accelerate our mission. As a Research Scientist, you will apply your deep scientific knowledge and research skills to advance paradigm-shifting research at a large scale. You will be at the heart of our efforts to deliver step-changes in the capabilities of our frontier models, with a significant focus on our Gemini Diffusion project. You will work in a tight-knit and highly collaborative team environment that fosters fundamental research and technical innovation, giving you hands-on experience with improving state-of-the-art AI systems. As a team member, your work may involve:

• Brainstorming new disruptive ideas that could become the next generation of frontier AI models, particularly within the text diffusion space.
• Prototyping and developing these ideas with the rest of the team, contributing directly to Gemini Diffusion research.
• Solving key research challenges by designing and executing experimental research on text diffusion models, sharing analyses, and proposing next steps.
• Rigorously validating the theoretical and practical impact of our work at a large scale.
• Working collaboratively with other Generative AI teams to move the technologies we develop out of the lab and into production.
• Advancing the fundamental architecture, algorithmic design, and capabilities of large-scale diffusion models.
• Bringing deep scientific expertise into our projects. You will share your insights and knowledge with other researchers and engineers. We take scientific rigor seriously, and you will be a steward of that ethos.

About you

We take a holistic view of people's backgrounds and do not expect you to be an expert in all areas. We invest heavily in training and development, and continual learning is a key part of the role. In order to set you up for success as a Research Scientist at Google DeepMind, we look for the following skills and experience:

• Advanced degree in computer science, electrical engineering, science, mathematics, or equivalent experience.
• Academic research experience in machine learning, publications, or research experience in related fields.
• Experience with some or all LLMs, Transformers, Diffusion models, Text diffusion, Large-scale distributed training.
• Strong communication skills (via discussion, presentation, technical and research writing, whiteboarding, etc.).
• Programming experience, particularly with Python-based scientific libraries such as Numpy, Scipy, JAX, PyTorch, or TensorFlow.
• Deep familiarity with the machine learning, mathematics, and statistics needed to follow relevant research papers (linear algebra, calculus, etc.) and reason about cutting-edge innovations.
• Agile and solution-focused mindset - be prepared to work on anything!

We're also interested in any of:

• A track record of building software, either in open source or as part of a company product or research papers.
• Large-scale system design, distributed systems.
• Distributed computation for ML, especially in the context of accelerators (e.g., sharding, multi-host computation).
• C++ or broader programming experience.
• Data engineering and visualisation.

Data Science Manager

Location: London (Hybrid) | Practice Area: Data & Analytics | Type: Permanent

Shape intelligent solutions. Lead with insight. Drive data innovation.

The Role

We’re looking for a Data Science Manager to lead innovative projects that apply data, AI, and machine learning to solve complex challenges across financial services. You’ll guide talented data professionals, collaborate closely with business stakeholders, and drive impactful, scalable solutions that deliver measurable business value.

What You’ll Do

• Lead data science teams to design, develop, and deploy advanced machine learning and AI solutions.
• Drive the adoption of cutting-edge technologies including generative AI, LLMs, and agentic AI frameworks.
• Collaborate with business and technology teams to align technical outcomes with strategic goals.
• Provide thought leadership and best practices across the data science lifecycle, from exploration to deployment.
• Mentor and develop data professionals, fostering a culture of innovation and excellence.

What We’re Looking For

• Proven experience leading the delivery of data science or AI projects from concept to production.
• Strong knowledge of Python and core ML libraries (e.g., spaCy, NumPy, SciPy, Transformers).
• Understanding of big data and cloud technologies (Spark, Hadoop, Azure, AWS, or GCP).
• Deep expertise in MLOps principles, scalable model deployment, and model governance.
• Excellent communication and stakeholder management skills with the ability to translate data insights into business value.

Bonus Points For

• MSc or PhD in a numerate discipline.
• Experience in Banking or Financial Services.
• Exposure to GenAI, LLMs, and intelligent agent workflows.
• Experience with DevOps, CI/CD, and productionising ML systems.
• A passion for mentoring and developing early-career data talent.

Why Join Capco

• Deliver innovative, high-impact data solutions for Tier 1 financial institutions.
• Work in a collaborative, entrepreneurial consulting environment.
• Access continuous learning, training, and industry certifications.
• Join a growing global Data Practice of 800+ experts driving transformation.
• Be part of a culture where individuality, creativity, and collaboration are celebrated.

We offer a competitive, people-first benefits package designed to support every aspect of your life:

• Core Benefits: Discretionary bonus, competitive pension, health insurance, life insurance and critical illness cover.
• Mental Health: Easy access to CareFirst, Unmind, Aviva consultations, and in-house first aiders.
• Family-Friendly: Maternity, adoption, shared parental leave, plus paid leave for sickness, pregnancy loss, fertility treatment, menopause, and bereavement.
• Family Care: 8 complimentary backup care sessions for emergency childcare or elder care.
• Holiday Flexibility: 5 weeks of annual leave with the option to buy or sell holiday days based on your needs.
• Continuous Learning: Minimum 40 hours of training annually-choose workshops, certifications, or e-learning-your growth, your way. Business Coach assigned from Day One for one-on-one guidance.
• Healthcare Access: Convenient online GP services.
• Extra Perks: Gympass (Wellhub), travel insurance, Tastecard, season ticket loans, Cycle to Work, and dental insurance.

Inclusion at Capco

We’re committed to a barrier-free, inclusive recruitment process. If you need any adjustments at any stage, just let us know -we’ll be happy to help. We welcome applicants from all backgrounds. At Capco, we value the difference you make, and the differences that make you. Our #BeYourselfAtWork culture champions diversity, equity, and inclusion, and we bring a collaborative mindset to everything we do #LI-DNI

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

About the Role:

iSAM Helix is an Equities Statistical Arbitrage (StatArb) business line within iSAM Funds,
which trades 24/6 globally. iSAM Helix has been live since 2021 and continues to evolve
rapidly as part of an ambitious roadmap focused on expanding strategy breadth and
capacity. Helix consists of four groups: Research, Quantitative Development,
Technology and Data.
The project is highly collaborative; the team are looking for a Quantitative Developer
capable of working on all aspects of the trading platform - research, development, and
live trading platforms. Technology is a front-line function within Helix, playing a critical
role in systematic trading.
Both the research platform and the production trading system are built on top of
custom implementation of high-performance python graph (DAG). The same graph
framework is being used across the whole environment – research and back testing,
live trading, analytics, risk, position keeping and P&L.

Responsibilities:
The opportunity would involve tackling complex problems in which you’d be a key part
of team working on a large breadth of challenges, including the following:

• Develop and support a complex quantitative StatArb strategies involving large-
  scale data processing, sophisticated statistical modelling, portfolio construction
  and highly optimised execution.
• Build and maintain systems handling highly diversified equity portfolios.
• Monitoring transaction costs and behaviour of a high turnover strategy.
• Process and analyse vast historical datasets for research and back-testing,
  alongside real-time, tick-level market data for live trading.
• Contribute to the design and use of a high-performance, graph-based (DAG)
  framework enabling concurrent data processing for research and production.
• Monitor and manage execution quality, transaction costs and market risks
  arising from changing market regimes and small statistical effects.
• Work closely with quantitative researchers to enhance tooling, frameworks and
  shared feature libraries.
• Take ownership of system components in a fast-paced, agile environment,
  working both independently and collaboratively as required.
• Participate in live trading support, including interaction with orders and brokers
  as part of a rota (FCA certification required).

Qualifications:
3 years’ experience in a technical role within the finance industry (investment
bank, hedge fund and associated firms)

• Degree in Mathematics or Physics preferred; other STEM subjects such as
  Computer Science will also be considered.
• Python: Strong software developer with in-depth knowledge and experience.
• Numpy (including numba): in-depth knowledge is required.
• Strong knowledge of Unix systems (processes, memory, I/O).
• Deep understanding of statistical methods, numerical optimisation and equity
  market microstructure.
• Experience working with graph-based (DAG) data processing frameworks.

Personal Attributes:

• Highly analytical with a strong sense of ownership and accountability.
• Comfortable tackling complex, ambiguous problems with limited oversight.
• Collaborative mindset with the ability to work closely with researchers, technologists and trading operations.
• Calm and reliable under pressure, particularly in live trading environments.