The Role

Quantitative research is a key driver of innovation at CTC and one of the pillars upon which our firm is built. As a Quantitative Researcher, you’ll operate near the tip of the spear in a collaborative, dynamic environment. This includes close partnership with other researchers, traders, and engineers on quantitative problem-solving, trading strategy generation, back-testing, statistical analysis, and system design. Our environment of collaborative innovation and intellectual curiosity allows us to share in our victories while continually challenging ourselves to stretch the limits of our creativity. Take advantage of this opportunity to apply the scientific method to business problems as part of one of our Quant teams at CTC! 

We prioritize team matching at the outset of our hiring process, thoughtfully considering which of our two teams (Vol Overlay or Delta Force) offers the best fit for each candidate’s strengths and interests while also aligning to the firm’s highest priority needs. 

What We’re Looking For   

We are seeking a Quantitative Researcher who can seamlessly blend academic rigor with practical application in our fast-paced trading environment. This individual will partner with our Trading and Technology teams to strengthen, scale, and evolve the firm's trading capabilities. The ideal candidate will possess a unique combination of analytical prowess, programming skills, and eye for business, driving innovation and results in quantitative finance. 

Responsibilities 

• Analyze market data to come up with economic and microstructure hypotheses 
• Build predictive and explanatory models to describe financial markets 
• Add revenue by applying thorough research processes to real life business problems 
• Contribute to ongoing improvement of research and trading infrastructure 

Qualifications 

• PhD in Science or Engineering fields (e.g. Statistics, Mathematics, Applied Mathematics, or Operations Research) 
• Proven ability to conduct independent, high-quality research 
• Exceptional ability to communicate complex ideas and research results, both in writing and verbally 
• Unwavering commitment to quality, coupled with a drive for delivering commercial outcomes. 
• Demonstrated expertise in applying quantitative modeling techniques to large, complex datasets 
• Strong track record of publications in an industry setting 
• Advanced Python programming skills 

Nice to Have 

• Proficiency in C++ 
• Experience in financial markets 
• Experience using NumPy and Pandas libraries 
• Experience with the software development lifecycle 

Who You Are:

Working as part of the derivatives engineering team, you are an expert on data pipelining and API development. You have knowledge surrounding common derivatives pricing frameworks and inputs for different tradable assets, and how these inputs are derived. You also have experience with working with various backend technologies and have a detailed working knowledge of core software engineering concepts, such as garbage collection, asynchronous processing, and data structures. You have experience in using mathematical and financial libraries (i.e. SciPy, NumPy, QuantLib) in software engineering applications. You are also familiar with building deployment processes for applications, including unit testing, integration testing, and deployment to a cloud provider (EC2, Kubernetes). You have a curiosity for learning new technologies and expanding your expertise across business lines and technology stacks.

As a team member, you will also work on production support issues and be involved in improvements on CI/CD automation and DevOps. 

Knowledge of the following is an advantage:

• Python, Go, Java
• Derivatives Pricing Models (SABR, SVI)
• Kafka, AWS SQS, or MQ
• Relational and non-relational Databases (Postgres, SQL Server, Databricks)
• Time series databases
• Spark
• FastAPI, Pydantic
• Jenkins
• AWS
• Caching Strategies and Implementations
• In-Memory Data Management
• Experience with Docker

What You’ll Do:

• Work closely with the Derivatives trading desk in optimizing their trading and risk management tools, as well as building reusable derivatives pricing libraries and algorithms
• Embrace and champion the thoughtful adoption of AI to improve team performance and business outcomes.
• Leverage AI tools (e.g., generative AI, automation platforms, data copilots) to improve productivity, decision-making, and output quality in your day-to-day work.

What We’re Looking For: 

• 6+ years of professional experience working in software development
• Experience with building data pipelines, APIs, and reporting tools
• Experience in Financial Technology
• Strong knowledge of data structures, their implementations, and optimization techniques
• University degree in computer science, physics, engineering, or equivalent programming experience

Bonus Points: 

• Experience with LLM Finetuning and RAG Optimization
• Full lifecycle development of a commercial system, including: requirements definition, agile planning, releasing, and production support
• Experience in quantitative trading

What We Offer:

• Competitive base salary and discretionary bonus
• Hybrid/Flexible Working Arrangements 
• Flexible Time Off (paid)
• 3% 401(k) company contribution
• Company-paid health and protective benefits for employees, partners, and other dependents
• Generous paid Parental Leave
• Competitive family planning benefits for US employees 
• Opportunities to learn about the Crypto industry
• Smart, entrepreneurial, and fun colleagues
• Free daily snacks and weekly breakfasts/lunches 
• Employee Resource Groups
• Free coaching and counseling sessions through Headspace

Apply now and join us on our mission to engineer a new economic paradigm.

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 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 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.

DRW is a major Chicago-based proprietary trading firm founded in 1992 by Don Wilson, specializing in diversified, technology-driven market-making and quantitative trading across asset classes including fixed income, options, derivatives, commodities, energy, equities, FX, and cryptocurrency.

DRW is building out a dedicated prediction markets desk focused on platforms such as Polymarket and Kalshi. As a Prediction Markets Trader, you will develop, execute, and optimize high-conviction trading strategies in binary event contracts. You will manage a live portfolio, targeting consistent positive expectancy through market making, microstructure exploitation, cross-platform arbitrage, event-driven momentum, and statistical models. This role requires genuine, demonstrated passion for prediction markets, strong quantitative reasoning, and the ability to operate in thin, volatile, event-resolution-driven environments.

Core Responsibilities:

• Monitor and trade active markets in real time across Polymarket (CLOB/Gamma/Subgraph APIs) and Kalshi (FIX/WebSocket/REST).
• Execute strategies including: market making with dynamic skew, microstructure arbitrage (order-flow and book-imbalance sniping), cross-platform arb, news/event momentum (sub-second reaction), and statistical pairs/mean-reversion.
• Develop and backtest models using historical tick data, Bayesian probability updates, NLP sentiment parsing, and ML for fair-value estimation.
• Collaborate with engineering on low-latency infrastructure (API integrations, order engines, anomaly detection).

Required Qualifications:

• Bachelor's or higher in Quantitative Finance, Statistics, Computer Science, Economics, Mathematics, or equivalent.
• Strong programming skills: Python (pandas, NumPy, backtesting).
• Solid foundation in probability, statistics, time-series analysis, and Bayesian methods.
• Hands-on experience with prediction market platforms (Polymarket and/or Kalshi APIs) or closely related domains (options, binary events, sports/event betting).
• Genuine, demonstrated interest in prediction markets — we expect you to be actively engaged with the space (personal trading, deep reading of protocols, following major resolutions, contributing to discussions, etc.). This is non-negotiable.

Highly Valued (but not strictly required):

• Prior profitable trading experience in prediction markets, options, or event-driven strategies (personal or professional).
• Familiarity with blockchain/DeFi tools (ethers.js, Polygon RPC, USDC wallets).
• Experience with low-latency systems, FIX protocol, or Web3 integrations.
• Track record of building and backtesting quantitative models with real historical data.
• Deep domain knowledge of high-impact events (politics, macroeconomics, climate, sports).

Who We’re Looking For: We are especially interested in exceptionally sharp, self-motivated individuals — including strong campus hires and new graduates — who are obsessed with prediction markets and can demonstrate clear, substantive engagement with the space. If you’ve been actively trading Polymarket/Kalshi, analyzing resolutions, building personal models, or following the ecosystem closely, we want to talk to you.

Apply With: 

• Resume
• Cover letter explicitly detailing your genuine interest in prediction markets (specific examples of your engagement: trades you’ve made, resolutions you’ve studied, models you’ve built, protocols you follow, etc.)
• GitHub, personal blog, or portfolio links showing relevant work

Applications reviewed on a rolling basis. Strong candidates will receive a technical screen, strategy discussion, and live coding/modeling exercise focused on real prediction market scenarios.

Location:  Flexible.  US-based preferred.

The annual base salary range for this position is $175,000 to $200,000 depending on the candidate’s experience, qualifications, and relevant skill set. The position is also eligible for an annual discretionary bonus.  In addition, DRW offers a comprehensive suite of employee benefits including group medical, pharmacy, dental and vision insurance, 401k (with discretionary employer match), short and long-term disability, life and AD&D insurance, health savings accounts, and flexible spending accounts.

For more information about DRW's processing activities and our use of job applicants' data, please view our Privacy Notice at https://drw.com/privacy-notice.

California residents, please review the California Privacy Notice for information about certain legal rights at https://drw.com/california-privacy-notice.

#LI-GV1

Mid-level Applied AI Data Scientist (Tableau Focus)

Location: New York, NY (Hybrid – 3 days in-office) | Practice Area: Technology & Engineering | Type: Permanent

Turn data into insight, and insight into impact.

The Role
We are looking for a Data Scientist to join us, working at the intersection of data, machine learning, and business insight. In this role, you will apply statistical and machine learning techniques to real-world problems, helping clients unlock value from complex datasets. You will collaborate with cross-functional teams and contribute to the development of scalable, data-driven solutions.

What You’ll Do

• Apply statistical analysis, clustering, and probabilistic techniques to generate actionable business insights
• Work with structured and semi-structured datasets to identify patterns, trends, and anomalies
• Build and support NLP workflows, including named entity recognition (NER), entity resolution, and text classification
• Develop machine learning models with guidance from senior team members, contributing to evaluation and refinement
• Create Tableau dashboards and visualizations to communicate insights to technical and non-technical stakeholders

What We’re Looking For

• 3–7 years of experience in data science, analytics, or applied machine learning
• Strong foundation in statistics, probability, and core machine learning techniques (e.g., regression, classification, clustering)
• Hands-on experience with Python and libraries such as pandas, NumPy, and scikit-learn
• Experience building Tableau dashboards to clearly communicate data insights
• Ability to collaborate across teams and translate analytical findings into business-relevant outcomes

Bonus Points For

• Experience working with graph-like or network datasets
• Exposure to ML Ops practices such as experiment tracking, model versioning, and monitoring
• Hands-on experience with NLP techniques such as entity extraction or text processing
• Familiarity with cloud-based data or ML platforms
• Experience contributing to rapid prototyping or iterative AI solution development

Why Join Capco

• Deliver high-impact technology solutions for Tier 1 financial institutions
• Work in a collaborative, flat, and entrepreneurial consulting culture
• Access continuous learning, training, and industry certifications
• Be part of a team shaping the future of digital financial services
• Help shape the future of digital transformation across FS & Energy.

Use of Artificial Intelligence in Talent Acquisition
At Capco, we use artificial intelligence (AI) tools to support and enhance several parts of talent acquisition. This includes using AI-enabled features within LinkedIn to help source potential candidates, speeding up routine recruitment communications such as emails and creating compelling and brand-aligned job postings that accurately reflect role requirements, and AI-scheduling applications to improve the efficiency of interview coordination.

AI is used as a support tool only. All hiring decisions are made by talent acquisition and hiring teams.

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

Benefits

• Medical, Dental, Vision coverage
• 401(k) with employer match
• Maternity and paternity leave, plus dependent care support
• Tuition reimbursement and wellness reimbursement programs
• HSA, FSA, commuter benefits, and employee discount marketplace access

Inclusion at Capco
We’re committed to making our recruitment process accessible and straightforward for everyone. If you need any adjustments at any stage, just let us know – we’ll be happy to help. We value each person’s unique perspective and contribution. At Capco, we believe that being yourself is your greatest strength. Our #BeYourselfAtWork culture encourages individuality and collaboration – a mindset that shapes how we work with clients and each other every day.

We have been informed of several recruitment scams targeting the public. We strongly advise you to verify identities before engaging in recruitment related communication. All official Capco communication will be conducted via a Capco recruiter.

#LI-MB1

#LI-HYBRID

Who we are

About Stripe

Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career.

What you’ll do

About the internship

Stripe's Applied ML, Data Science, Risk, and Payments organizations are excited to offer PhD machine learning engineering internships for the summer of 2026. This is an exceptional opportunity to contribute to critical projects that directly enhance Stripe's suite of products, focusing on areas such as foundation models used for dozens of tasks e.g. fraud detection, enhanced support, and predicting user behavior.

As an intern, you'll tackle challenging problems at the intersection of finance, technology, and data. You'll have the chance to work on creative projects like the Stripe Assistant and the Stripe Foundation Model, which leverage machine learning to revolutionize how businesses interact with financial services and data.

Responsibilities

• Develop and deploy large-scale machine learning systems that drive significant business value across various domains.
• Engage in the end-to-end process of designing, training, improving, and launching machine learning models.
• Write production-scale ML models that will be deployed to help Stripe enable economic infrastructure access for a diverse range of businesses globally.
• Collaborate across teams to incorporate feedback and proactively seek solutions to challenges.
• Rapidly learn new technologies and approaches, demonstrating a strong ability to ask insightful questions and communicate the status of your work effectively.

Who you are

Minimum requirements

• A deep understanding of computer science, obtained through the pursuit of a PhD in Computer Science, Machine Learning, or a closely related field, with the expectation of graduating in winter 2026 or spring/summer 2027.
• Practical experience with programming and machine learning, evidenced by projects, classwork, or research. Familiarity with languages such as Python, Scala, Spark and libraries such as Pandas, NumPy, and Scikit-learn.
• Expertise in areas of machine learning such as supervised and unsupervised learning techniques, ML operations, and possibly experience in Large Language Models or Reinforcement Learning.
• Demonstrated ability to work on collaborative projects, with experience in receiving and applying feedback from various stakeholders.
• A proactive approach to learning unfamiliar systems and a demonstrated ability to understand complex systems independently.
• Intent to return to the degree-program after the completion of the internship/co-op.

Preferred qualifications

You Might Also Have:

• Two years of university education or equivalent experience, with in-depth knowledge in specific domains of machine learning.
• Published and presented peer-reviewed articles in top-tier venues.
• Experience in writing high-quality pull requests, maintaining good test coverage, and completing projects with minimal defects.
• Familiarity with navigating new codebases and managing work across different programming languages.
• Excellent written communication skills to clearly articulate your work to both team members and wider Stripe audiences.

Application requirements

Please submit the following with your application:

• A detailed resume or LinkedIn profile showcasing your work history.
• Examples of relevant work and your approach to learning, such as GitHub repositories, StackOverflow contributions, or other project portfolios.

Join us for an unforgettable summer internship and help shape the future of global commerce. At Stripe, you won't just be working on theoretical projects; you'll make a tangible impact on the world's economic infrastructure.

Polar Operations LLC (dba IMC Markets) has multiple openings for Python Software Engineer (REQ#4461661101) in Chicago, IL and Brooklyn, NY.

Your Core Responsibilities

• Implement software features and components for IMC's trading systems (25%).
• Design software solutions independently and make architectural decisions (10%).
• Debug and fix software issues in trading systems (5%).
• Identify complex multi-component issues, perform root cause analysis, and implement preventative solutions (5%).
• Ensure code quality and system reliability through comprehensive automated testing (10%).
• Contribute to the automated testing framework, own critical trading system components, and ensure reliability, performance, and scalability across regions (5%).
• Participate in code reviews (10%).
• Monitor system performance and trading operations (5%).
• Collaborate with traders and other teams to understand requirements and deliver solutions (10%).
• Participate in planning, estimate complexity of tasks, and help balance technical debt with feature development (5%).
• Mentor and guide junior developers and interns, helping them understand IMC's systems and development practices (10%).

Partial telecommuting permitted. Multiple positions available. Requisition #: 4461661101

Your Skills and Experience

This position requires a Bachelor’s degree, or foreign equivalent, in Computer science, Computer Engineering, or a similarly quantitative and technical field and one (1) year of experience in the job offered or a related occupation.

Must have at least one (1) year of experience in each of the following skill(s):

• Applying analytical and engineering techniques to solve complex problems programmatically;
• Programming with Python;
• Developing and implementing algorithms and data structures;
• Software development lifecycle and best practices;
• Designing and developing software applications in a collaborative, cross-functional environment;
• Experience with DevOps, databases, big data, or frontend frameworks;
• Experience with Docker, Kubernetes, and Linux environments;
• Experience working with financial data;
• Foundational knowledge of quantitative trading concepts and equity/index options;
• Exposure to web/API frameworks such as FastAPI and React;
• Experience with automated testing and CI/CD pipelines;
• Experience collaborating with trading desks and developing software for use in a quantitative trading environment;
• Experience with the following tools: Team City, JIRA ticket management, Gerrit code review tool, GitLab, uv, Gitlab CI, py-spy, memray, and Python Packaging; and
• Experience with the following libraries: Pandas, Polars, NumPy, Tensorflow, Scikit, scikit-learn, cvxpy, and Pytest.

#LI-DNI

The Team

Discretionary & Client Solutions Technology is ~35 engineers across London, New York, and Sofia, building the platforms that power Man Group's discretionary investment and client facing operations. We operate at high tempo — shipping multiple production releases weekly across portfolio analytics, fund data platforms, client reporting, data pipelines, dashboards, and AI tools.

We are one of the most active AI-adopting engineering teams in Man Group — building LLM-powered agents, research tools with vector search, and AI integrations that our portfolio managers and analysts use daily. You'll have the opportunity to shape how AI is integrated into investment workflows.

The Role

This is a senior engineering role sitting at the intersection of Man Group's Discretionary (public markets) and Solutions technology teams in New York. You will be the primary NY-based engineer supporting portfolio managers, analysts and quants functions across both business lines.

The role spans Python data pipelines and analytics platforms serving Discretionary investment teams — equities, credit, and alternatives — alongside Python systems powering Solutions' fund analytics, portfolio management, and reporting infrastructure. You'll work hands-on building and operating production systems while acting as the key technical liaison for NY-based stakeholders.

Our Technology Stack

• Python (primary), TypeScript/React
• Data: Pandas, NumPy, Kafka
• Backend: FastAPI, Flask
• Frontend: React, Streamlit dashboards, Tableau
• Infrastructure: Kubernetes, Airflow
• AI tooling: Claude Code, LLM agents, vector search, RAG — we actively build and ship AI tools for our investment teams

Key Responsibilities 

Development & Delivery (70%)

• Build, extend, and maintain Python data pipelines using Pandas, NumPy, and internal libraries
• Develop and enhance portfolio analytics, risk reporting, and fund data platforms
• Contribute to AI-powered tools for investment teams — research databases with vector search, AI integrations for portfolio managers and analysts
• Build and maintain FastAPI and Flask backends and React/TypeScript frontends using our shared component libraries
• Deploy services to Kubernetes; manage Airflow DAGs for scheduled data workloads
• Collaborate with London and Sofia-based engineers on cross-team initiatives

Stakeholder Engagement (20%)

• Serve as the primary technical contact for NY-based Discretionary and Solutions stakeholders
• Gather requirements, translate business needs into technical solutions, and manage expectations
• Work directly with portfolio managers, analysts, and quants — understanding their workflows is as important as writing the code

Production Operations (10%)

• Own production stability for systems in your portfolio — investigate data quality issues, triage support requests, manage incident response
• Maintain documentation and operational processes

Key Competencies 

Essential

• 5+ years of professional software engineering experience with a strong delivery track record
• Strong Python: Well-tested, modular production code. Comfortable with dataclasses, type hints, OOP, design patterns
• Financial services experience — particularly portfolio management, risk, or investment operations
• Pandas/NumPy proficiency: Building efficient data pipelines and transformations at scale
• AI/LLM tooling — experience building with or integrating LLM-based tools. We're active early adopters of AI-assisted development and are building AI agents for our investment teams
• Solid testing discipline: pytest, unit tests, integration tests — you write tests as a matter of course
• Comfortable in a Linux environment with Git, virtual environments, and CLI tooling
• Strong communicator: You can explain technical decisions to non-technical stakeholders concisely, and you view stakeholder interaction as integral to good engineering — not overhead
• Self-directed: You manage your own priorities, flag blockers early, and drive work to completion with appropriate autonomy
• Degree in a STEM subject or equivalent practical experience

Advantageous  

• React/TypeScript for frontend development
• Experience with web APIs: Building and consuming RESTful services (FastAPI, Flask, or equivalent)
• C#/.NET familiarity — some Solutions systems are built in .NET. You won't be the primary .NET engineer, but being able to read and navigate the codebase is valuable
• Kubernetes & containerisation — deploying and troubleshooting services in k8s
• Airflow — building and maintaining scheduled data pipelines
• Distributed systems concepts — messaging architectures, event-driven design, caching strategies
• Experience working with geographically distributed teams — London will be your primary collaboration hub

About the Position 

As a Data Scientist on the platform prediction team, you'll translate our probability of success predictions into measurable portfolio-level outcomes. You'll architect core systems — order management, execution simulation, portfolio construction, risk monitoring, and performance attribution — that let us rigorously evaluate signals from our AI-driven predictions in public and private equities and our internal portfolio.

This role sits at the intersection of quantitative finance, healthcare data, and AI-driven drug development. If you're excited about applying portfolio construction and risk management fundamentals to one of the most consequential prediction problems in healthcare, this is the role.No other company — hedge fund or pharma — has a technical data science position translating drug development experience into durable AI-native portfolio strategies. The skills you develop here — portfolio construction over assets with radically asymmetric risk profiles, clinical trial analytics, AI/ML in production, and risk management across multi-year horizons — can directly impact the delivery of new and effective therapeutics to patients by best aligning impactful medicines with economic incentives.

Responsibilities

• Work with the team to implement and maintain core portfolio engine: order management system, execution simulation layer, portfolio construction service, and performance tracking
• Design risk frameworks that quantify exposure across a portfolio of drug development bets with radically different risk profiles, timelines, and failure modes
• Run rigorous backtesting experiments with strict temporal constraints to evaluate Formation strategies against baseline approaches and measure marginal signal from new evidence sources
• Coordinate across the organization to integrate internal Formation data sources (clinical trial data, genomic evidence, real-world data) and proprietary tooling into portfolio analytics pipelines
• Work with product and engineering teams to build dashboards and reporting that communicate portfolio performance, risk metrics, and strategy comparisons to both technical and executive stakeholders
• Collaborate with the broader data science team to ensure portfolio-level evaluation feeds back into model improvement and evidence prioritization

About You 

Required Qualifications

• MS or PhD in a quantitative field (statistics, finance, physics, computational science, engineering, or related)
• 1-3 years in a quantitative research, data science, or analytics role — finance, healthcare, academic research, or consulting all count; substantive internships qualify
• Strong Python programming skills with experience in data-intensive workflows (pandas, numpy, scipy)
• Solid grasp of core portfolio construction and risk concepts: position sizing, rebalancing, Sharpe ratio, drawdown, volatility, benchmark comparison
• Demonstrated ability to work with messy, real-world datasets — comfortable with data wrangling, deduplication, and quality assessment
• Clear communicator who can present quantitative results to both technical peers and business stakeholders

Preferred Qualifications

• Experience with backtesting frameworks or portfolio simulation (vectorbt, Backtrader, or custom implementations)
• Exposure to healthcare, pharma, or biotech data (clinical trials, claims data, -omics, real-world evidence)
• Familiarity with alternative data in a research or investment context
• Experience with probability-of-success modeling, drug development decision analysis, or health economics
• Comfort with LLMs or AI/ML pipelines in a production or research setting
• Familiarity with dashboard/visualization tools (Streamlit, Plotly, Dash) and pipeline orchestration (Dagster, Airflow)

Healthcare OR finance domain knowledge is valued; both are not required.

Total Compensation Range: $154,500 - $202,000

Quantitative research is a key driver of innovation at CTC and one of the pillars upon which our firm is built. We are seeking a Quantitative Researcher to partner with Trading and Technology to strengthen, scale, and evolve the firm's trading capabilities within one of the quant research teams. As a Quantitative Researcher, you will be embedded on a research desk, working close to the tip of the spear in a dynamic environment. This includes partnership with other researchers, traders and engineers on quantitative problem solving, trading strategy generation, back-testing, statistical analysis, and system design. Our environment of collaborative innovation and intellectual curiosity allows us to share in our victories while continually challenging ourselves to stretch the limits of our creativity. Take advantage of this opportunity to apply the scientific method to business problems as part of the Quant team at CTC! 

What You’ll Do

• Analyze market data to come up with economic and microstructure hypotheses 
• Build predictive and explanatory models to describe financial markets 
• Add revenue by applying thorough research processes to real life business problems 
• Conduct independent, high quality research in quantitative finance 
• Communicate complex ideas and research results effectively, both in writing and verbally 
• Drive innovation and results through analytical prowess and business acumen 

What We’re Looking For

• PhD in Science or Engineering fields (e.g. Statistics, Mathematics, Physics, Applied Mathematics, Operations Research, Electrical Engineering) strongly preferred 
• Minimum 5 years of experience as a Quantitative Researcher in a top systematic trading team 
• Demonstrable track record of generating positive PnL 
• Advanced programming skills and experience with the software development lifecycle 
• Proven ability to blend academic rigor with practical application in fast-paced trading environments 
• Unwavering commitment to quality, coupled with a drive for delivering commercial outcomes 
• Python skills including Numpy and Pandas libraries 

Nice to Haves

• Experience with a wide variety of market and alternative data  
• Expertise in US options markets, options pricing models, volatility surfaces, and risk management techniques  
• Strong track record of publications in an industry setting 

Data at Brex

The Data organization develops insights, models, and data infrastructure for teams across Brex, including Sales, Marketing, Product, Engineering, and Operations. Our Data Scientists, Analysts, and Engineers work together to make data—and insights derived from data—a core asset across the company.

What you’ll do

As a Data Analyst II (DA), you will play a central role in enhancing the operational tracking and reporting capabilities of different business teams across Brex. You will work closely with Data Scientists, Data Engineers, and partner teams to drive meaningful insights for the business through visualizations, self-service tools, and ad-hoc analyses. This is a high-impact role in a fast-paced fintech environment where your work will directly influence strategic decisions.

Where you’ll work

This role will be based in our São Paulo office. We are a hybrid environment that combines the energy and connections of being in the office with the benefits and flexibility of working from home. We currently require a minimum of three coordinated days in the office per week, Monday, Wednesday and Thursday. As a perk, we also have up to four weeks per year of fully remote work!

Responsibilities

• Apply data visualization and storytelling skills in creating business intelligence solutions (such as Looker and/or Hex dashboards) that enable actionable insights.
• Perform ad-hoc analyses and deep dives to investigate business questions, surface trends, and provide data-driven recommendations.
• Develop self-service data tools and processes that empower business stakeholders to independently monitor the performance and health of their respective areas.
• Collaborate closely with Data Scientists and Data Engineers to identify data sources, enable data pipelines, and support the development of analytical data models that operationalize reports and dashboards.
• Implement and maintain rigorous data quality checks to ensure the integrity and robustness of datasets used across dashboards, reports, and analyses.
• Partner with various departments—including Sales, Operations, Product, and Finance—to understand their data needs and deliver tailored analyses and reporting that support strategic planning.
• Contribute to the automation of recurring analyses and reporting workflows using Python.

Requirements

• 4+ years of experience in data analytics or a related role in a professional setting.
• 3+ years of experience working directly with Sales, Operations, Product, or equivalent business teams.
• Fluency in SQL to manipulate data and perform complex analyses (CTEs, window functions, joins across large datasets).
• Proficiency in Python for data analysis, automation, and scripting (Pandas, NumPy, and similar libraries).
• Experience with business intelligence and data visualization tools (Looker, Hex, Tableau, or similar).
• Strong quantitative and analytical skills with a demonstrated ability to translate data into business insights.
• Strong communication skills and the ability to work effectively with stakeholders across different functions and levels of technical fluency.
• Experience with generative AI and LLM-based tools (Claude Code, Cursor, GitHub Copilot) to perform and accelerate analyses, automated reporting, and build self-service data tools.

Bonus points

• Familiarity with cloud data platforms (e.g., Snowflake, BigQuery, Databricks).
• Familiarity with dbt for data modeling and transformation.
• Exposure to data pipeline orchestration tools (e.g., Airflow).
• Experience in fintech, financial services, or payments.
• Comfort operating in a fast-paced, high-growth environment with evolving priorities.

Brex LLC is a wholly owned subsidiary of Capital One, N.A.

Data at Brex

The Data organization develops insights, models, and data infrastructure for teams across Brex, including Sales, Marketing, Product, Engineering, and Operations. Our Data Scientists, Analysts, and Engineers work together to make data—and insights derived from data—a core asset across the company.

What you’ll do

As a senior Data Analyst (DA III), you will own the end-to-end analytics lifecycle for one or more business areas at Brex. You’ll go beyond building dashboards—you’ll frame the right questions, design rigorous analyses, apply statistical methods, and translate your findings into clear recommendations for leadership. You will also serve as a technical leader on the Data Analytics team, mentoring more junior analysts and helping define the standards and best practices that elevate the team’s work.

This role sits at the intersection of analytics, analytics engineering, and business strategy. You’ll work in a modern data stack environment and partner closely with Data Scientists, Data Engineers, and senior leaders across the organization.

Where you’ll work

This role will be based in our San Francisco office. We are a hybrid environment that combines the energy and connections of being in the office with the benefits and flexibility of working from home. We currently require a minimum of three coordinated days in the office per week, Monday, Wednesday and Thursday. As a perk, we also have up to four weeks per year of fully remote work!

Responsibilities

• Own the analytics lifecycle for assigned business areas: from problem framing and data sourcing through analysis, insight generation, and stakeholder presentation.
• Build and maintain dashboards and self-service reporting tools that enable business teams to independently track performance, identify risks, and make data-driven decisions.
• Write production-quality SQL and Python code to extract, transform, and analyze data at scale.
• Collaborate with Data Engineers and Data Scientists to develop and maintain analytical data models, improve data pipelines, and ensure data quality across the organization.
• Partner with leadership across Sales, Operations, Product, Finance, and other departments to identify high-impact analytical opportunities and deliver actionable recommendations.
• Mentor other data analysts and contribute to the development of team standards, documentation, code review practices, and analytical frameworks.
• Proactively identify gaps in data infrastructure, propose improvements, and contribute to the evolution of the team’s tooling and processes.

Requirements

• 5+ years of experience in data analytics, business intelligence, or a related quantitative role.
• 3+ years of experience partnering directly with Sales, Operations, Product, or equivalent business teams as an embedded analytics partner.
• Advanced SQL proficiency, including CTEs, window functions, performance optimization, and working across complex data models.
• Proficiency in Python for data analysis, automation, and modeling (Pandas, NumPy, scikit-learn, or similar).
• Experience with cloud data warehouses, particularly Snowflake (BigQuery and Databricks also valued).
• Hands-on experience with BI and data visualization tools (Looker, Tableau, Hex, or similar).
• Strong stakeholder management skills—proven ability to present complex technical findings to non-technical audiences.
• Experience with generative AI and LLM-based tools (Claude Code, Cursor, GitHub Copilot) to perform and accelerate analyses, automated reporting, and build self-service data tools.

Bonus points

• Demonstrated experience applying statistical methods to business problems (e.g., regression, classification, A/B testing).
• Experience with dbt for data modeling and transformation.
• Experience building and maintaining data pipelines using orchestration tools such as Airflow.
• Experience working with APIs for data ingestion and integration.
• Familiarity with version control systems (Git).
• Experience in fintech, financial services, or payments.
• Track record of leading cross-functional analytics projects from scoping through delivery.

Compensation

The expected salary range for this role is $114,192 - $142,740. However, the starting base pay will depend on a number of factors including the candidate’s location, skills, experience, market demands, and internal pay parity. Depending on the position offered, equity and other forms of compensation may be provided as part of a total compensation package.

Brex LLC is a wholly owned subsidiary of Capital One, N.A.

Data at Brex

The Data organization develops insights, models, and data infrastructure for teams across Brex, including Sales, Marketing, Product, Engineering, and Operations. Our Data Scientists, Analysts, and Engineers work together to make data—and insights derived from data—a core asset across the company.

What you’ll do

As a senior Data Analyst (DA III), you will own the end-to-end analytics lifecycle for one or more business areas at Brex. You’ll go beyond building dashboards—you’ll frame the right questions, design rigorous analyses, apply statistical methods, and translate your findings into clear recommendations for leadership. You will also serve as a technical leader on the Data Analytics team, mentoring more junior analysts and helping define the standards and best practices that elevate the team’s work.

This role sits at the intersection of analytics, analytics engineering, and business strategy. You’ll work in a modern data stack environment and partner closely with Data Scientists, Data Engineers, and senior leaders across the organization.

Where you’ll work

This role will be based in our New York office. We are a hybrid environment that combines the energy and connections of being in the office with the benefits and flexibility of working from home. We currently require a minimum of three coordinated days in the office per week, Monday, Wednesday and Thursday. As a perk, we also have up to four weeks per year of fully remote work!

Responsibilities

• Own the analytics lifecycle for assigned business areas: from problem framing and data sourcing through analysis, insight generation, and stakeholder presentation.
• Build and maintain dashboards and self-service reporting tools that enable business teams to independently track performance, identify risks, and make data-driven decisions.
• Write production-quality SQL and Python code to extract, transform, and analyze data at scale.
• Collaborate with Data Engineers and Data Scientists to develop and maintain analytical data models, improve data pipelines, and ensure data quality across the organization.
• Partner with leadership across Sales, Operations, Product, Finance, and other departments to identify high-impact analytical opportunities and deliver actionable recommendations.
• Mentor other data analysts and contribute to the development of team standards, documentation, code review practices, and analytical frameworks.
• Proactively identify gaps in data infrastructure, propose improvements, and contribute to the evolution of the team’s tooling and processes.

Requirements

• 5+ years of experience in data analytics, business intelligence, or a related quantitative role.
• 3+ years of experience partnering directly with Sales, Operations, Product, or equivalent business teams as an embedded analytics partner.
• Advanced SQL proficiency, including CTEs, window functions, performance optimization, and working across complex data models.
• Proficiency in Python for data analysis, automation, and modeling (Pandas, NumPy, scikit-learn, or similar).
• Experience with cloud data warehouses, particularly Snowflake (BigQuery and Databricks also valued).
• Hands-on experience with BI and data visualization tools (Looker, Tableau, Hex, or similar).
• Strong stakeholder management skills—proven ability to present complex technical findings to non-technical audiences.
• Experience with generative AI and LLM-based tools (Claude Code, Cursor, GitHub Copilot) to perform and accelerate analyses, automated reporting, and build self-service data tools.

Bonus points

• Demonstrated experience applying statistical methods to business problems (e.g., regression, classification, A/B testing).
• Experience with dbt for data modeling and transformation.
• Experience building and maintaining data pipelines using orchestration tools such as Airflow.
• Experience working with APIs for data ingestion and integration.
• Familiarity with version control systems (Git).
• Experience in fintech, financial services, or payments.
• Track record of leading cross-functional analytics projects from scoping through delivery.

Compensation

The expected salary range for this role is $114,192 - $142,740. However, the starting base pay will depend on a number of factors including the candidate’s location, skills, experience, market demands, and internal pay parity. Depending on the position offered, equity and other forms of compensation may be provided as part of a total compensation package.

Brex LLC is a wholly owned subsidiary of Capital One, N.A.

Jump Trading Group is committed to world class research. We empower exceptional talents in Mathematics, Physics, and Computer Science to seek scientific boundaries, push through them, and apply cutting edge research to global financial markets. Our culture is unique. Constant innovation requires fearlessness, creativity, intellectual honesty, and a relentless competitive streak. We believe in winning together and unlocking unique individual talent by incentivizing collaboration and mutual respect. At Jump, research outcomes drive more than superior risk adjusted returns. We design, develop, and deploy technologies that change our world, fund start-ups across industries, and partner with leading global research organizations and universities to solve problems.

Jump’s Client Market Making business provides clients with direct access to our liquidity across a wide range of asset classes in all market conditions. Leveraging our proprietary pricing platform, we deliver fully customizable and disclosed liquidity solutions designed to meet the unique needs of each of our clients.

As a Trading Services Specialist in our Client Market Making business, you will play a key role in onboarding clients, supporting global platform operations, and collaborating with business development, product, technology, and back-office teams to enhance the client experience.

This role is based in either Chicago, Illinois or New York, New York.

What You'll Do:

• Manage the entire client onboarding process including connectivity, session setup, conformance testing, and pilot trades.
• Monitor and resolve production issues to ensure a seamless client trading experience.
• Collaborate with developer and production reliability engineer teams to identify workflow and system issues, document/prioritize tickets, and deliver solutions.
• Partner with trading, product, and sales teams to turn client requests into actionable roadmap items.
• Create and maintain clear up-to-date documentation that enables team-wide knowledge sharing.

Skills You Need:

• Bachelor’s degree with demonstrated experience in a fast-paced, client-facing trading environment.
• 3 to 6 years of relevant experience working with trading systems, order entry protocols, market data protocols, troubleshooting technical issues and providing production support.
• Strong understanding of the client onboarding lifecycle, including FIX protocol, conformance testing, and network routing.
• Product expertise in at least one asset class (e.g., FX, CFDs, equities, fixed income).
• Proven ability to successfully lead and complete technical projects.
• Experience with data analysis using tools like Python (Pandas, NumPy), SQL, or KDB+.
• Flexibility to collaborate across time zones, including occasional off-hours work.

Benefits include:

• Private Medical, Vision and Dental Insurance
• Travel Medical Insurance
• Group Pension Scheme
• Group Life Assurance and Income Protection Schemes
• Paid Parental Leave
• Parking and Commuter Benefits

Your Impact on our Mission

Zocdoc’s most important asset is our people. As a Staff Data Scientist, Marketplace, you’ll play a meaningful role in transforming healthcare by shaping how millions of patients discover and book care.

The Marketplace team is responsible for driving patient demand, optimizing the search and booking experience, and ensuring a healthy, high-performing two-sided marketplace. This includes areas such as Growth, Search, Insurance, and Patient Home.

As a strategic technical leader on the Marketplace Analytics team, you’ll design and scale analytical frameworks that inform product and growth strategy, guide experimentation, and optimize performance across the patient funnel—from acquisition through booking and retention. Your work will directly improve marketplace liquidity, efficiency, and long-term value.

You’ll enjoy this role if you are…

• Passionate about transforming healthcare through data and turning complex datasets into meaningful product insights

• A force multiplier who loves mentoring and enabling teams to deliver scalable, high-impact work

• Comfortable operating at the intersection of business strategy, data science, and product innovation

• Energized by complex, ambiguous problems and skilled at translating them into structured analytical solutions

• Personally motivated by building systems, frameworks, and capabilities that outlast any one analysis

• Serious about your work, but not about yourself — you value rigor and humility equally

Your day to day is…

• Partnering with Product, Marketing, Finance, Engineering, and Commercial teams to translate insights into actionable product and business strategy

• Architecting and executing experimentation frameworks, including A/B testing design, power analysis, variance reduction, and advanced causal inference methodologies (e.g., DiD, synthetic controls, propensity modeling, causal forests)

• Identifying, designing, and guiding the development of analytical models (e.g., LTV, survival, uplift models) to improve provider utilization, acquisition, retention, patient engagement, and client ROI

• Establishing scalable statistical frameworks and best practices to quantify the impact of product and commercial initiatives

• Partnering with Engineering to ensure data quality, event instrumentation, feature availability, and scalable pipelines that enable trustworthy analysis

• Mentoring and upskilling analysts and data scientists, raising the bar for analytical rigor and impact across Zocdoc

• Advancing AI-assisted analytical workflows to streamline recurring analysis and decision support

• Working with cutting edge GenAI tools and technology

You’ll be successful in this role if you have…

• An unrelenting desire to build more equitable, inclusive, and diverse workplaces, and view this role as an opportunity to create positive change

• 8+ years of experience in data science, machine learning, or related quantitative roles

• Proven success developing LTV models, survival models, uplift models, or similar predictive frameworks for customer targeting and optimization

• Deep expertise in SQL and Python (pandas, NumPy, scikit-learn, statsmodels)

• Strong knowledge of experimentation and causal inference, including statistical power analysis, experiment design, and quasi-experimental methodologies

• Experience shaping and scaling analytics functions—not just building individual models

• Experience working in cross-functional product organizations

• The ability to integrate generative AI tools into daily workflows to automate tasks, foster innovation, and maximize productivity

• Superb communication skills and the ability to influence non-technical stakeholders

• The mentality of an entrepreneur/owner with a strong bias to action

• Humility — you treat all people with dignity and respect, regardless of title or tenure

Nice to have

• Master’s or PhD in Statistics, Economics, Applied Math, or another quantitative field

• Experience within a SaaS organization

Benefits

• Flexible, hybrid work environment at our convenient Soho location

• Unlimited Vacation

• 100% paid employee health benefit options (including medical, dental, and vision)

• Commuter Benefits

• 401(k) with employer funded match

• Corporate wellness program with Wellhub

• Sabbatical leave (for employees with 5+ years of service)

• Competitive paid parental leave and fertility/family planning reimbursement

• Cell phone reimbursement

• Catered lunch everyday along with beverages and snacks

• Employee Resource Groups and ZocClubs to promote shared community and belonging

• Great Place to Work Certified

AI is becoming vitally important in every function of our society. At Scale, our mission is to accelerate the development of AI applications. For 8 years, Scale has been the leading AI data foundry, helping fuel the most exciting advancements in AI, including: generative AI, defense applications, and autonomous vehicles. With our recent Series F round, we’re accelerating the usage of frontier data and models by building complex agents for enterprises around the world through our Scale Generative Platform (SGP).

The SGP ML team works on the front lines of this AI revolution. We interface directly with clients to build cutting edge products using the arsenal of proprietary research and resources developed at Scale. As an Applied AI Engineer, you’ll work with clients to create ML solutions to satisfy their business needs. Your work will range from building next-generation AI cybersecurity firewalls to creating transformative AI experiences in journalism to applying foundation genomic models making predictions about life-saving drug proteins. Daily data-driven experiments will provide key insights around model strengths and inefficiencies which you’ll use to improve your product’s performance. If you are excited about shaping the future of the modern AI movement, we would love to hear from you!

You will:

• Own, plan, and optimize the AI behind our Enterprise customer’s deepest technical problems
• Leverage SGP to build the most advanced AI agents across the industry including multimodal functionality, tool-calling, and more
• Have experience gathering business requirements and translating them into technical solutions 
• Meet regularly with customer teams onsite and virtually, collaborating cross-functionally with all teams responsible for their data and ML needs
• Push production code in multiple development environments, writing and debugging code directly in both our customer’s and Scale’s codebases.
• Be able and willing to multi-task and learn new technologies quickly

Ideally you'd have:

• 7+ years of full-time engineering experience, post-graduation
• A love for solving deeply complex technical problems with ambiguity using state of the art research and AI to accomplish your client’s business goals
• Strong engineering background: a Bachelor’s degree in Computer Science, Mathematics, or another quantitative field or equivalent strong engineering background.
• Deep familiarity with a data-driven approach when iterating on machine learning models and how changes in datasets can influence model results
• Experience working with cloud technology stack (eg. AWS or GCP) and developing machine learning models in a cloud environment
• Proficiency in Python to write, test and debug code using common libraries (ie numpy, pandas)

Nice to haves:

• Strong knowledge of software engineering best practices
• Have built applications taking advantage of Generative AI in real, production use cases
• Familiarity with state of the art LLMs and their strengths/weaknesses

Job Description

A highly collaborative, fast-growing team, Point72 Internal Alpha Capture (IAC) is developing scalable quantitative equity trading signals that leverage rigorous research, state-of-the-art machine learning methods, a broad range of public and proprietary data sources, and unparalleled computing power.

We are looking for exceptional students to join us as quantitative developer interns for Summer 2025. Our interns will work closely with our team, receive comprehensive, in-depth training, and help develop novel signals that may have real impact.

You will gain exposure to a variety of activities, which may include:

• Enhancing quantitative research platforms by benchmarking and integrating in-house and cloud technologies
• Optimizing data ETL pipelines, persistent/in-memory caches, and SQL databases
• Improving research and trading tools and infrastructure

Desirable Candidates

• Undergraduate or higher degree in Computer Science, Machine Learning, or other quantitative discipline
• Strong programming experience in Python with production-level coding quality
• Experience with Unix environment and shell scripting
• Experience with cloud computing, ideally AWS and Databricks
• Experience with numerical Python libraries (e.g. Numpy, Pandas, PyTorch, etc.)
• Knowledge of version control (Git) and software CI/CD tools and lifecycle
• Knowledge of profiling (e.g. cProfile, SnakeViz, memory-profiler, etc.) and code optimization is a plus
• Knowledge of statistics and machine learning is a plus
• Willing to take ownership of his/her work, working both independently and within a small team
• Prior experience in the financial services industry is not required
• Commitment to the highest ethical standards

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

Role/Responsibilities: 

We are passionate about data. We collaborate to build elegant, effective, scalable and highly reliable solutions to empower predictive modelling in finance.

Cubist’s data services group is looking for a junior Quantitative Software Developer to join our dedicated team. Our group is responsible for the timely delivery of comprehensive and error-free data to some of the most demanding and successful systematic Portfolio Managers in the world.

This exceptional individual will be a member of a small team of data and software developers who play a vital role in ensuring the smooth day-to-day implementation of a large research infrastructure, and the live production trading of billions of dollars of capital across global capital markets, including equities, futures, options and other financial instruments. 

Responsibilities include:

• Building processes and technology tools to ingest, tag and clean datasets.
• Assisting Data Scientists with data processing, enrichment, and product development.
• Contributing to existing infrastructure and applications primarily written in Python, but also Go and C++.
• Monitoring and enhancing the automated data collection and cleansing infrastructure.
• Researching new technologies for improved data management and efficient retrieval.

Requirements:

• B.S. or higher in computer science, engineering or a relevant quantitative field such as Mathematics, Statistics, Physics.
• Proficiency in Python and its ecosystem (numpy, pandas, polars, scikit-learn), with an understanding of Python and library internals
• Proficiency with Go and/or C++ is not required but is a big plus
• Hands-on experience with software architecture and engineering best practices (testing, CI/CD, monitoring, profiling, version control)
• Strong problem-solving skills, ability to analyze and solve intricate problems, optimize code, and develop efficient solutions in a fast-paced environment.
• Intellectual curiosity and a love of learning.
• Strong oral and written communication skills.
• Commitment to the highest ethical standards.

About Cubist

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

Role

Quantitative researcher to help build out a systematic macro (futures, FX, and vol) strategies. Core focus will be working on mid-frequency alpha strategies.

Job Description

• Develop systematic trading models across FX, commodities, fixed income, and equity markets
• Alpha idea generation, backtesting, and implementation
• Assist in building, maintenance, and continual improvement of production and trading environments
• Evaluate new datasets for alpha potential
• Improve existing strategies and portfolio optimization
• Execution monitoring
• Be a core contributor to growing the investment process and research infrastructure of the team

Desirable Candidates

• Masters or PhD in mathematics, statistics, physics or other quantitative discipline. PhD in statistics or machine learning is a plus
• Experience in quantitative trading, ideally in FX or futures
• Experience with alpha research, portfolio construction and optimization
• Experience building statistical/technical, fundamental, and data driven signals
• Experience synthesizing predictive signals for both cross-sectional and time-series models
• Strong experience with data exploration, dimension reduction, and feature engineering
• Thorough understanding of and comfort using a variety of regression techniques—including OLS, MLS, Ridge, Lasso, and Bayesian inference—as well as techniques for dealing with errors that can occur, such as auto-correlation and heteroskedasticity
• Experience managing and running risk is a strong plus
• Proficiency in Python using the machine learning stack—numpy, pandas, scikit-learn, etc.
• Creative mindset
• Strong time management ability—the ability to manage multiple tasks and deadlines in a fast-paced environment
• High degree of drive and energy—must be a self-starter
• Ability to work cooperatively with all levels of staff and to thrive in a team-oriented environment
• Commitment to the highest ethical standards and who act with professionalism and integrity at all times

The annual base salary range for this role is $150,000-$200,000 (USD) , which does not include discretionary bonus compensation or our comprehensive benefits package. Actual compensation offered to the successful candidate may vary from posted hiring range based upon geographic location, work experience, education, and/or skill level, among other things.

ABOUT CUBIST:

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

RESPONSIBILITIES:

• Building components for both live trading and simulation
• Refining and increasing automation and robustness of the research infrastructure including alpha estimation, risk modeling, and backtesting components
• Building tools for signal blending, simulation, portfolio construction, the research framework, and dashboards
• Maintaining and updating the platform, ensuring its stability, robustness, and security
• Developing robust data checking and storage procedures
• Troubleshooting and resolving any systems related issues and handle the release of code fixes and enhancements

REQUIREMENTS:

• Bachelor’s degree or higher in computer science or other STEM discipline
• Advanced proficiency in Python and its ecosystem (numpy, pandas, polars, scikit-learn), with an understanding of Python and library internals
• Experience contributing to core Python numerical libraries is a huge plus (numpy, tensorflow, torch, jax)
• Proficiency with Linux
• Hands-on experience with software architecture and engineering best practices (testing, CI/CD, monitoring, profiling, version control)
• Strong quantitative and analytical skills; command of linear algebra, statistics, and machine learning would be helpful
• Proficiency with C/C++ is a plus
• Experience with designing and implementing trading systems is a plus
• Commitment to the highest ethical standards

Join our team as Sr. Engineer in the systematic vol trading space. Lead the development of a cutting-edge options research and trading platform that directly influences our market position and drives pnl. Bridge the gap between development, research and trading teams to deliver technical solutions that give us a market edge.

What You’ll Do

• Develop, test, and maintain high-performance trading applications, backtesting tools, and libraries using Python, with a focus on volatility products.
• Work closely with traders to translate strategies into technical requirements, and with researchers to optimize the integration of models into live trading systems.
• Create and drive a technical roadmap developing strong, dependable, and easy-to-maintain code in accordance with established guidelines and industry norms.
• Participate in code reviews, provide constructive feedback, and contribute to continuous improvement within the team.
• Keep up-to-date with the latest advancements in trading technology, Python development, and related libraries and frameworks.

What We’re Looking For

• Significant experience in working directly on a systematic trading desk. Options experience strongly preferred.
• Experience in an architect-level role.
• Hands-on experience with Python and proficiency in modern Python concepts such as asyncio.
• Experience designing and implementing systems capable of processing real-time market data at low latencies and integrating seamlessly with research pipelines.
• Experience designing and implementing high-performance and flexible research systems capable of hosting and processing terabytes of data on a computer cluster with GPU and tens of thousands CPU cores.
• Experience using numerical toolkits such as pandas and NumPy is preferred but not required.

At Rockstar Games, we create world-class entertainment experiences. 

Become part of a team working on some of the most rewarding, large-scale creative projects to be found in any entertainment medium - all within an inclusive, highly-motivated environment where you can learn and collaborate with some of the most talented people in the industry. 

Rockstar is on the lookout for an experienced Data Scientist to join our Analytics team to scale our Game Security and Trust & Safety capabilities. In this role, you'll develop sophisticated detection systems, establish community safety metrics, and leverage advanced analytics to protect our player communities through data visualization, anomaly detection, supervised learning, and community health measurement.

This is a full-time, in-office position based out of Rockstar’s NYC headquarters in Downtown Manhattan. 

WHAT WE DO

Partner with Trust & Safety and Game Security teams to conduct high-impact projects that shape player safety policies, inform strategy, and ensure regulatory compliance (GDPR, DSA, OSA). Develop detection systems, advanced analytics models (graph analytics, NLP), and scalable machine learning applications protecting millions of players. 

RESPONSIBILITIES

• Drive complex investigations and data-driven strategies addressing cheating, griefing, toxicity, and harassment at scale. 
• Develop and automate detection solutions for cheats, exploits, and violations with Game Security team. 
• Serve as subject matter expert on Trust & Safety metrics, regulatory compliance, and transparency reporting. 
• Design sophisticated detection systems balancing player safety with user experience using rule-based and ML approaches. 
• Translate complex analytical findings into actionable insights for technical and non-technical audiences, including executives. 
• Establish and monitor Trust & Safety and Anti-Cheat KPIs with dashboards enabling data-driven decisions. 
• Mentor junior team members and advance analytical best practices. 

REQUIREMENTS

• Bachelor's in STEM field (Computer Science, Data Science, Statistics, Mathematics); advanced degree preferred. 
• 5+ years in data science/analytics with expertise in Security, Anti-Cheat, Trust & Safety, or related domains. 
• Strong SQL proficiency with large-scale databases. 
• Advanced Python, PySpark, and data science tools (numpy, pandas, scikit-learn) in cloud production environments. 
• Required expertise in one: graph analytics for coordinated behavior, NLP for content moderation/toxicity, or network analysis for community safety. 
• Experience with Trust & Safety metrics, transparency reporting, and regulatory frameworks (GDPR, DSA, OSA). 
• Exceptional communication and stakeholder management skills with ability to influence executive strategy. 
• Expert data storytelling—translating sophisticated analytics into clear narratives driving policy decisions. 
• Strategic thinking balancing player safety, user experience, and business objectives. 
• Passion for creating safe, inclusive gaming communities. 

PLUSES

Please note that these are desirable skills and are not required to apply for the position.

• Trust & Safety and/or Anti-Cheat experience at gaming, social media, or UGC platforms. 
•  Real-time detection systems and streaming analytics experience. 
• Advanced ML Techniques (Transformers, LLMs, GenAI) for content moderation. 
• Graph analytics for coordinated behavior detection. 
• Published research or thought leadership in Trust & Safety, content moderation, or online community safety.  
• Experience with big data technologies (PySpark) and cloud platforms (AWS, GCP, Azure, Databricks).  
• Multilingual capabilities or experience with non-English content moderation challenges. 

HOW TO APPLY

Please apply with a CV and cover letter demonstrating how you meet the skills above. If we would like to move forward with your application, a Rockstar recruiter will reach out to you to explain next steps and guide you through the process.

Rockstar is committed to creating a work environment that promotes equal opportunity, dignity and respect. In line with this commitment, Rockstar will provide reasonable accommodations to qualified job applicants with disabilities during the recruitment process in order for such applicants to be considered for the position for which they are applying, as well as to qualified employees to enable them to perform the essential functions of their roles. If you need more information about Rockstar’s reasonable accommodation policies or process, or need to request an accommodation, please notify your recruiter during the interview process.  

If you’ve got the right skills for the job, we want to hear from you. We encourage applications from all suitable candidates regardless of age, disability, gender identity, sexual orientation, religion, belief, race, or any other protected category.

#LI-SD1

About Us

AXQ Capital is a global quantitative investment firm with offices in New York, Beijing, Shanghai, and Hong Kong. We pursue consistent alpha through rigorous scientific research and sustained investment in technology and data infrastructure. Our strategies are deployed across global markets, spanning multiple geographies, asset classes, and trading horizons.

Job Duties 

As a Machine Learning Researcher, you will develop ML/DL models to generate alpha from large-scale financial and alternative datasets. Working closely with portfolio managers and senior quantitative researchers, you will conduct research across a range of trading strategies within a fast, iterative research-feedback loop.

Qualifications

Below is a list of skills and experiences we believe are relevant. Even if you don’t consider yourself a perfect match, we still encourage you to apply because we are committed to helping our people grow and develop.

• Master’s or PhD from a top-tier university in a quantitative discipline (e.g., mathematics, physics, statistics, computer science, or related fields)
• Strong foundation in machine learning, statistics, and optimization, with deep expertise in at least one area such as time series modeling, NLP, or LLMs
• Strong communication skills and ability to collaborate effectively in a research-driven environment
• Experience with the Python scientific and ML ecosystem (e.g., NumPy, Pandas/Polars, PyTorch, TensorFlow)
• Proven ability to build and improve models that perform under noisy, non-stationary, and high-dimensional data conditions
• Intellectually curious, highly analytical, and driven to discover alpha in complex systems
• Self-motivated and highly productive, with strong ownership and a bias toward action
• Publications at top-tier venues such as NeurIPS, ICML, KDD, or IJCAI
• Strong track record in competitive ML platforms (e.g., Kaggle) or academic competitions
• Prior experience in quantitative research, systematic trading, or alpha signal generation

About the Role:

K Health is looking for a Strategic Insights Analyst with an AI-first mindset to drive better decisions, faster. This role sits at the intersection of operations, data science, and AI-powered automation, making it ideal for someone who can combine rigorous analytical thinking applied to business intuition, while leveraging cutting-edge AI tools to generate insights and translate them into action.

You'll play a pivotal role in shaping K Health's growth by working cross-functionally with Product, Operations, Marketing, and Finance teams to inform our strategic roadmap. This role requires someone who can think like a top-tier business consultant but execute like a data scientist—leveraging SQL, Python, AI agents, and data-driven decision-making to solve high-impact business problems at scale.

This is a high-impact individual contributor role, perfect for someone who thrives in a fast-paced, highly collaborative, and AI-enhanced environment.

Unfortunately, this position does not provide immigration support or sponsorship at this time. 

What you will do:

• Apply analytical rigor and AI-powered tools to strategic business problems, uncovering actionable insights that drive key company metrics through both traditional analysis and AI augmentation.
• Enable self-serve analytics and empower stakeholders to access data to facilitate data-driven decision making at scale
• Partner cross-functionally with Clinical Operations, Marketing, Product and Finance teams to identify opportunities, develop hypotheses, and execute in-depth analyses using both traditional and AI-enhanced methods.
• Develop and own key performance metrics, leveraging AI tools to automate monitoring, anomaly detection, and insight generation.
• Leverage SQL and Python through AI agents to analyze large datasets more efficiently, build data models, and create self-updating dashboards that help scale decision-making.
• Use statistics, data science techniques, and AI tools (e.g., regression analysis, forecasting, clustering, LLM-powered analysis) to drive better predictions and recommendations.
• Build and deploy AI-powered analysis workflows using command line agents that can execute complex SQL queries, perform Python-based analysis, and generate insights autonomously.
• Communicate insights effectively, using AI tools to help transform complex data into crisp, actionable recommendations for leadership and stakeholders.
• Develop scalable operational processes that leverage our data assets in creative ways using data-driven techniques, large language models, automated pipelines, and AI agents.

What we are looking for:

• 4-6 years of experience in analytics, strategy, consulting, business operations, or a related field, with demonstrated experience leveraging AI tools for productivity gains.
• AI First Mindset—proven track record of identifying and implementing AI-powered solutions to enhance analytical workflows and business processes.
• Strong SQL proficiency—ability to write complex queries and manipulate large datasets, with experience using AI tools to enhance SQL workflow efficiency.
• Solid Python knowledge (e.g., pandas, NumPy, scikit-learn) with experience using Python in conjunction with AI agents and automation tools.
• Experience with AI-powered analysis tools—familiarity with command line AI agents, LLM-based coding assistants, and automated analysis pipelines.
• Solid foundation in statistics and data science concepts (e.g., hypothesis testing, regressions, forecasting) with understanding of how AI can augment these techniques.
• Highly analytical and metrics-driven, with the ability to define KPIs, size opportunities, and measure business performance using both traditional and AI-enhanced methods.
• Strong strategic problem solver—able to break down ambiguous problems and apply a first-principles approach while leveraging AI for faster iteration.
• Excellent communication skills—able to translate data into compelling, actionable insights, using AI tools to enhance visualization and storytelling.
• Scrappy and resourceful—you find a way to get things done, often by creatively applying AI tools to multiply your impact.
• Fast learner—you can quickly grasp new concepts, tools, AI technologies, and business models.

Bonus: 

• Experience with BI tools (e.g., Looker, Tableau, Mode) and their AI-enhanced features
• Familiarity with machine learning concepts and MLOps
• Experience with measuring clinical outcomes
• Experience with prompt engineering and LLM optimization
• Exposure to A/B testing methodologies and automated experimentation platforms
• Experience building or deploying AI agents for business analysis
• Knowledge of AI workflow automation tools (e.g., Langchain, AutoGPT, or similar)

Benefits & Perks:  #LI-Hybrid

• Hybrid work schedule with weekly lunches and stocked fridges 
• Monthly social committees for company events
• 18 vacation days, 9 company holidays, 5 sick days, and 2 personal days 
• Stock options for every full-time employee 
• Paid parental leave
• 401k benefit
• Commuter Benefits 
• Competitive health, dental, and vision insurance options 

Company Overview

Soros Fund Management LLC (SFM) is a global asset manager and family office founded by George Soros in 1970. With $28 billion in assets under management (AUM), SFM serves as the principal asset manager for the Open Society Foundations, one of the world’s largest charitable foundations dedicated to advancing justice, human rights, and democracy.

Distinct from other investment platforms, SFM thrives on agility, acting decisively when conviction is high and exercising patience when it’s not. With permanent capital, a select group of major clients, and an unconstrained mandate, we invest opportunistically with a long-term view in a wide range of strategies and asset classes, including public and private equity and credit, fixed income, foreign exchange, and alternative assets. Our teams operate with autonomy, while cross-team collaboration strengthens our conviction and empowers us to capitalize on market dislocations.

At SFM, we foster an ownership mindset, encouraging professionals to challenge the status quo, innovate, and take initiative. We prioritize development, enabling team members to push beyond their roles, voice bold ideas, and contribute to our long-term success. This culture of continuous growth and constructive debate fuels innovation and drives efficiencies.

Our impact is measured by both the returns we generate and the values we uphold, from environmental stewardship to social responsibility. Operating as a unified team across geographies and mandates, we remain committed to our mission, ensuring a meaningful, lasting impact.

Headquartered in New York City with offices in Greenwich, Garden City, London, and Dublin, SFM employs 200 professionals.

Team Overview

The Quantitative Development and Strategy team is responsible for research and analytics technology at SFM. We work closely with the front office and across SFM to provide solutions across many areas of quantitative finance. 

Job Overview

We are seeking an equity focused Quantitative Strategist to partner with our portfolio managers and researchers to generate insights that drive investment strategies. You will combine mathematical techniques with core engineering skills to build analytics that can scale our investment process. This role emphasizes empirical research and development. Success requires creativity in formulating the business problem, disciplined research, the ability to communicate findings, and deploying the finished analytical tools to investment decision-makers. 

Major Responsibilities

• Partner with our portfolio managers and analysts to solve problems where quantitative models, technology, and AI can enhance research, operations, and decision making. 

• Conduct data-driven research across diverse asset classes to uncover patterns, relationships, and predictive signals. 

• Contribute to our production-grade analytical tools and libraries that are incorporated into daily investment and risk-management workflows.
• Quantitative support for desk projects such as reporting, back testing, development and implementation of new models. 

• Be the primary liaison between tech. infrastructure and our fundamental portfolio managers in delivering the above 

• Document research methods, results, and best practices for use across the investment team. 

What We Value  

• Master’s or PhD degree in a STEM field preferred.

• 3+ years of work experience in a quantitative finance role, preferably equities.
• Strong foundation in probability, statistics, linear algebra, calculus and other commonly used mathematical techniques.

• Proficiency in Python and exposure to modern data science libraries (Pandas, NumPy, Scikit-learn, PyTorch, TensorFlow, etc.). 

• Experience with machine learning, NLP, and quantitative research methods. 

• Excellent communication skills targeting technical and non-technical audiences. 

We anticipate the base salary of this role to be between $150,000-200,000. In addition to a base salary, the successful candidate will also be eligible to receive a discretionary year-end bonus. 

In all respects, candidates need to reflect the following SFM core values:

Smart risk-taking   //   Owner’s Mindset   //   Teamwork   //   Humility   //   Integrity    

Quantitative research is a key driver of innovation at CTC and one of the pillars upon which our firm is built. We are seeking a Principal Quantitative Researcher to partner with Trading and Technology to drive new revenue, scale, and evolve the firm's trading capabilities. In this role, you will lead research areas, influencing the direction of the team in a dynamic environment. This includes partnership with other researcher managers, traders and engineers on quantitative problem solving, trading strategy generation, back-testing, statistical analysis, and system design. 

Take advantage of this opportunity to apply the scientific method to business problems as part of the Quant team at CTC! 

What You’ll Do

• Define and articulate a long-term vision that will lead to new sources of revenue, evolving with business needs and market structure 
• Conduct commercially focused revenue generating research, while supporting others with their research 
• Develop a structured roadmap and ensure quant functions remain focused, aligned, and accountable 
• Direct development of innovative infrastructure across pricing models and research platforms 
• Foster coordination across risk management, development, and quantitative research to drive measurable business impact 
• Provide thought leadership while applying academic rigor to practical trading applications  

What We’re Looking For

• PhD in Science or Engineering fields (e.g. Statistics, Mathematics, Physics, Operations Research, Electrical Engineering) strongly preferred 
• Experience in a top systematic trading team of which at least 10 years as a quantitative researcher 
• Proven ability to conduct independent, high-quality research 
• Demonstrable track record of generating positive PnL 
• Exceptional ability to communicate complex ideas and research results, both in writing and verbally 
• Experience with the software development lifecycle with advanced programming skills 
• Unique combination of analytical prowess, programming skills, and acute understanding of business 
• Unwavering commitment to quality, coupled with a drive for delivering commercial outcomes 
• Strong Python skills including Numpy and Pandas libraries 

Nice to Haves

• Management experience leading a healthy and empowered team, driving accountability. 
• Experience with a wide variety of market and alternative data  
• Expertise in US options markets, options pricing models, volatility surfaces, and risk management techniques  
• Strong Python skills including Numpy and Pandas libraries  
• Strong track record of publications in an industry setting 

Company Overview

Soros Fund Management LLC (SFM) is a global asset manager and family office founded by George Soros in 1970. With $28 billion in assets under management (AUM), SFM serves as the principal asset manager for the Open Society Foundations, one of the world’s largest charitable foundations dedicated to advancing justice, human rights, and democracy.

Distinct from other investment platforms, SFM thrives on agility, acting decisively when conviction is high and exercising patience when it’s not. With permanent capital, a select group of major clients, and an unconstrained mandate, we invest opportunistically wITh a long-term view in a wide range of strategies and asset classes, including public and private equity and credit, fixed income, foreign exchange, and alternative assets. Our teams operate with autonomy, while cross-team collaboration strengthens our conviction and empowers us to capitalize on market dislocations.

At SFM, we foster an ownership mindset, encouraging professionals to challenge the status quo, innovate, and take initiative. We prioritize development, enabling team members to push beyond their roles, voice bold ideas, and contribute to our long-term success. This culture of continuous growth and constructive debate fuels innovation and drives efficiencies.

Our impact is measured by both the returns we generate and the values we uphold, from environmental stewardship to social responsibility. Operating as a unified team across geographies and mandates, we remain committed to our mission, ensuring a meaningful, lasting impact.

Headquartered in New York City with offices in Greenwich, Garden City, London, and Dublin, SFM employs 200 professionals.

Team Overview

The Quantitative Development and Strategy team is responsible for research and analytics technology at SFM. We work closely with the front office and across SFM to provide solutions across many areas of quantitative finance. 

Job Overview

We are seeking a Quantitative Strategist to partner with our credit portfolio managers to generate insights that drive investment strategies and improve desk performance. This role emphasizes rigorous research, testing, and interpretation of results. Success requires creativity in scoping research problems, discipline in testing hypotheses, and the ability to communicate findings clearly to investment decision-makers.

Major Responsibilities

• Replace the desk’s legacy excel based infrastructure with modern, Python-based, architecture
• Assist with desk strategy and workflows
• Analyze large datasets (market, economic, alternative) to extract actionable insights that inform trading strategies
• Contribute to desk P&L and risk reporting infrastructure and reporting
• Work with our PM teams on quantitative research projects
• Partner with broader quant team to build out signal back-testing and data analysis infrastructure
• Build visualization tools for signal, research, and back-testing
• Automate research and order generation workflows

What We Value  

• Bachelor’s Degree in a STEM field. Advanced degree preferred.
• 5+ years of relevant work experience in a front office quantitative role
• Familiarity with credit markets, including investment‑grade, high‑yield, and CDS markets; strong understanding of credit curves, OAS/z‑spread measures, relative‑value frameworks, and bond‑level analytics such as DV01, carry/roll, and curve fitting.
• Exposure to structured products (CLO, ABS, RMBS) and concepts such as prepayment, credit migration, recovery assumptions, default modeling, or hazard rates is a strong plus.
• Strong proficiency in Python and scientific libraries (NumPy, Pandas, SciPy, scikit‑learn); capable of writing production‑quality code with testing and documentation.
• Experience working with modern compute and engineering stacks such as version control (Git), CI/CD pipelines, Docker, and workflow orchestration tools.
• Experience designing and testing predictive models with large financial datasets.
• Excellent communication skills targeting technical and non-technical audiences.

We anticipate the base salary of this role to be between $175,000-225,000. In addition to a base salary, the successful candidate will also be eligible to receive a discretionary year-end bonus. 

In all respects, candidates need to reflect the following SFM core values:

Smart risk-taking   //   Owner’s Mindset   //   Teamwork   //   Humility   //   Integrity    

The Role

We’re seeking a Senior Data Scientist to lead the science behind a best-in-class ticketing experience for fans, with a focus on the operational journey from ticket purchase through event entry. In this role, you will own and develop predictive and decisioning models that proactively identify and mitigate fulfillment issues, strengthen inventory validation, and optimize customer service policies — all while balancing fan experience with operational constraints.

You will work on problems where getting it right matters: predicting issues before they impact fans, identifying emerging pain points at scale, and turning moments of potential failure into opportunities to build trust and loyalty. This includes building and productionizing models on both structured and unstructured data, such as LLM-backed pipelines that extract actionable signals from customer communications and support interactions.

You will partner closely with product managers, analytics engineers, operations leaders, and other data scientists to translate ambiguous business problems into durable, production-ready data products, and to influence decisions that measurably improve the fan experience.

Location: Hybrid (3 days in office/2 days remote) – New York, NY or Century City, CA 

What You'll Do

• Own the science behind ticket fulfillment: Drive reliability, ease of use, and customer satisfaction by crafting and deploying scalable, production-grade machine learning models that directly inform operational systems and decisions.
• Drive data-informed strategy: Work with operations partners to shape roadmaps, using analysis and modeling to identify, prioritize, and size high-impact opportunities that can be implemented and sustained at scale.
• Design for validation: Apply principles of experimentation and causal inference to ensure work products can be rigorously evaluated, defining offline validation and online testing strategies early in the design process.
• Build the data foundation: Partner with platform and analytics teams to ensure data availability and quality, including event instrumentation, batch and streaming ETL, feature stores, and monitoring for model performance, bias, and drift.
• Tell the story: Communicate trade-offs and impact to execs and non-technical partners; make the complex understandable and actionable.

What You've Done

• 5+ years of industry experience in data science or machine learning, with an MS or PhD in mathematics, statistics, computer science, or a related quantitative field preferred.
• Strong programming skills in Python, with experience using numerical and machine learning libraries such as Pandas, NumPy, SciPy, scikit-learn, and gradient-boosting frameworks (e.g., LightGBM, XGBoost).
• Demonstrated experience building, deploying, and iterating on production machine learning models in cloud environments (e.g., AWS, Azure), including post-deployment monitoring and improvement.
• Expertise working with large-scale data using modern analytics and compute platforms such as Snowflake, BigQuery, or Databricks, with strong proficiency in SQL.
• Proven ability to establish data science methodology in new or ambiguous domains, owning work end to end—from stakeholder alignment and problem framing to delivery and measurable impact.
• Excellent communication skills, with the ability to clearly articulate modeling assumptions, tradeoffs, and impact to both technical and non-technical audiences.

Nice to have:

• Experience applying machine learning to operational problem spaces such as ticket fulfillment, fraud detection, customer service, or trust and safety.
• Experience with production ML platforms and workflows, such as Metaflow or comparable systems (e.g., Airflow-based ML pipelines, Kubeflow, SageMaker Pipelines, Prefect, Flyte), including model versioning, scheduling, and monitoring.
• Experience selecting and applying appropriate causal inference approaches to evaluate model and policy impact, including methods such as uplift modeling, synthetic control, and BSTS.

What We Offer

• Accelerated Growth Environment: An environment designed for swift skill and knowledge enhancement, where you have the autonomy to lead experiments and tests on a massive scale.
• Top Tier Compensation Package: Competitive base, equity, and upside that tracks with your impact.
• Flexible Time Off: Enjoy unlimited Flex Time Off, giving you the flexibility to manage your schedule and take time to recharge as needed.
• Comprehensive Benefits Package: Prioritize your well-being with a comprehensive benefits package, featuring 401k, and premium Health, Vision, and Dental Insurance options.

The Role

We’re seeking a Senior Data Scientist to lead the science behind a best-in-class ticketing experience for fans, with a focus on the operational journey from ticket purchase through event entry. In this role, you will own and develop predictive and decisioning models that proactively identify and mitigate fulfillment issues, strengthen inventory validation, and optimize customer service policies — all while balancing fan experience with operational constraints.

You will work on problems where getting it right matters: predicting issues before they impact fans, identifying emerging pain points at scale, and turning moments of potential failure into opportunities to build trust and loyalty. This includes building and productionizing models on both structured and unstructured data, such as LLM-backed pipelines that extract actionable signals from customer communications and support interactions.

You will partner closely with product managers, analytics engineers, operations leaders, and other data scientists to translate ambiguous business problems into durable, production-ready data products, and to influence decisions that measurably improve the fan experience.

Location: Hybrid (3 days in office/2 days remote) – New York, NY or Century City, CA 

What You'll Do

• Own the science behind ticket fulfillment: Drive reliability, ease of use, and customer satisfaction by crafting and deploying scalable, production-grade machine learning models that directly inform operational systems and decisions.
• Drive data-informed strategy: Work with operations partners to shape roadmaps, using analysis and modeling to identify, prioritize, and size high-impact opportunities that can be implemented and sustained at scale.
• Design for validation: Apply principles of experimentation and causal inference to ensure work products can be rigorously evaluated, defining offline validation and online testing strategies early in the design process.
• Build the data foundation: Partner with platform and analytics teams to ensure data availability and quality, including event instrumentation, batch and streaming ETL, feature stores, and monitoring for model performance, bias, and drift.
• Tell the story: Communicate trade-offs and impact to execs and non-technical partners; make the complex understandable and actionable.

What You've Done

• 5+ years of industry experience in data science or machine learning, with an MS or PhD in mathematics, statistics, computer science, or a related quantitative field preferred.
• Strong programming skills in Python, with experience using numerical and machine learning libraries such as Pandas, NumPy, SciPy, scikit-learn, and gradient-boosting frameworks (e.g., LightGBM, XGBoost).
• Demonstrated experience building, deploying, and iterating on production machine learning models in cloud environments (e.g., AWS, Azure), including post-deployment monitoring and improvement.
• Expertise working with large-scale data using modern analytics and compute platforms such as Snowflake, BigQuery, or Databricks, with strong proficiency in SQL.
• Proven ability to establish data science methodology in new or ambiguous domains, owning work end to end—from stakeholder alignment and problem framing to delivery and measurable impact.
• Excellent communication skills, with the ability to clearly articulate modeling assumptions, tradeoffs, and impact to both technical and non-technical audiences.

Nice to have:

• Experience applying machine learning to operational problem spaces such as ticket fulfillment, fraud detection, customer service, or trust and safety.
• Experience with production ML platforms and workflows, such as Metaflow or comparable systems (e.g., Airflow-based ML pipelines, Kubeflow, SageMaker Pipelines, Prefect, Flyte), including model versioning, scheduling, and monitoring.
• Experience selecting and applying appropriate causal inference approaches to evaluate model and policy impact, including methods such as uplift modeling, synthetic control, and BSTS.

What We Offer

• Accelerated Growth Environment: An environment designed for swift skill and knowledge enhancement, where you have the autonomy to lead experiments and tests on a massive scale.
• Top Tier Compensation Package: Competitive base, equity, and upside that tracks with your impact.
• Flexible Time Off: Enjoy unlimited Flex Time Off, giving you the flexibility to manage your schedule and take time to recharge as needed.
• Comprehensive Benefits Package: Prioritize your well-being with a comprehensive benefits package, featuring 401k, and premium Health, Vision, and Dental Insurance options.

Company Overview

Soros Fund Management LLC (SFM) is a global asset manager and family office founded by George Soros in 1970. With $28 billion in assets under management (AUM), SFM serves as the principal asset manager for the Open Society Foundations, one of the world’s largest charitable foundations dedicated to advancing justice, human rights, and democracy.

Distinct from other investment platforms, SFM thrives on agility, acting decisively when conviction is high and exercising patience when it’s not. With permanent capital, a select group of major clients, and an unconstrained mandate, we invest opportunistically wITh a long-term view in a wide range of strategies and asset classes, including public and private equity and credit, fixed income, foreign exchange, and alternative assets. Our teams operate with autonomy, while cross-team collaboration strengthens our conviction and empowers us to capitalize on market dislocations.

At SFM, we foster an ownership mindset, encouraging professionals to challenge the status quo, innovate, and take initiative. We prioritize development, enabling team members to push beyond their roles, voice bold ideas, and contribute to our long-term success. This culture of continuous growth and constructive debate fuels innovation and drives efficiencies.

Our impact is measured by both the returns we generate and the values we uphold, from environmental stewardship to social responsibility. Operating as a unified team across geographies and mandates, we remain committed to our mission, ensuring a meaningful, lasting impact.

Headquartered in New York City with offices in Greenwich, Garden City, London, and Dublin, SFM employs 200 professionals.

Team Overview

The Quantitative Development and Strategy team is responsible for research and analytics technology at SFM. We work closely with the front office and across SFM to provide solutions across many areas of quantitative finance. 

Job Overview

We are seeking a talented Quantitative Strategist to join our team. You will work with the business as an individual contributor to deliver key projects with far-reaching impact on trading, alpha generation, risk management and more. You have Excellent problem-solving skills and the ability to collaborate with cross-functional teams. 

If you value a balanced approach that combines thoughtful innovation with high-quality execution, this opportunity offers the chance to play a key role in strengthening our infrastructure while contributing to our broader mission. 

Major Responsibilities

• Development of real time P&L and risk systems 

• Build interactive tools for our portfolio management teams 

• Work with portfolio managers on implementing trading signals across a wide range of asset classes 
• Partner with our portfolio managers and analysts to solve problems where AI and quant technology can enhance research, risk management, and decision making. 
• Quantitative support for desk projects such as reporting, back testing, development and implementation of new models and strategies

• Communicate complex technical concepts effectively to technical and non-technical stakeholders. 

What We Value  

• At least 2-5 years of experience in a front-office focused quantitative development, research, or strategist role 

• Advanced degree in Physics, Engineering, Math, Mathematical Finance, or related field. 

• Strong proficiency in Python and standard libraries (Pandas, NumPy. Etc.) 

• Exposure to other programming languages (C#, R, etc) 

• Proficiency with SQL 

We anticipate the base salary of this role to be between $150,000-200,000. In addition to a base salary, the successful candidate will also be eligible to receive a discretionary year-end bonus. 

In all respects, candidates need to reflect the following SFM core values:

Smart risk-taking   //   Owner’s Mindset   //   Teamwork   //   Humility   //   Integrity    

ABOUT THE TEAM

The data team delivers infrastructure and models to deploy valuable data across the business. Working closely with our researchers and traders, we build resilient and easily maintainable data models and pipelines. Additionally, our developers support live trading by maintaining pipeline operations and enhance our data platform by developing new frameworks, libraries, and services, thereby enhancing team efficiency, throughput, and code quality.

RESPONSIBILITIES 

• Gain a comprehensive understanding of investment research teams' data needs and provide the right solution to them
• Develop, test, and optimize Python data applications, frameworks, and services
• Collaborate with technologists and researchers to align data applications and platforms with evolving business needs
• Write and review technical documentation, including requirements for researchers and proposals for platform enhancements, as well as production support guidelines
• Frequently take the lead on production support operations

REQUIREMENTS

• Bachelor’s in a technology related field (e.g. Engineering, Computer Science, etc.)
• Strong skills programming in Python (inc. Numpy & Pandas) as well as significant experience with SQL, as a software developer, quantitative developer or data engineer
• Exposure to Relational database engineering or NoSQL database
• Experience with any of the following systems is a plus: Apache Airflow, Docker, Kubernetes
• Strong design, debugging and problem-solving skills
• Strong analytic and strategic thinking skills
• Strong communication skills

NICE TO HAVE

• Experience at either a hedge fund or for a trading group on the buy-side
• Experience with any of the following systems is a plus: Apache Airflow, Docker, Kubernetes

COMPENSATION

• Competitive compensation commensurate with level of experience.
• Comprehensive benefits package including medical, dental, vision, 401(k), insurance, Summer Fridays, and wellness reimbursement.
• Base Salary: $150,000 - $200,000/ yr plus bonus

About Swayable

Swayable is a fast-growing AI and automated data science platform that measures public opinion and the impact of messages and advertising content on it. We are a 40-person team backed by top technology and social impact investors, including Y Combinator. Founded in 2018 by physics PhDs, it is led by the former Executive Director for Digital Strategy at the New York Times. Clients include major consumer-facing brands (American Express, Airbnb, Paramount Pictures), technology companies (Anthropic, Meta, Amazon), academic researchers (MIT, Yale, Stanford) and mission-aligned civic advocacy campaigns (e.g. on climate, human rights and elections).

Joining Swayable means being on a team whose work changes the course of history. The technology we develop is at the leading edge of transforming some of the world’s most important campaign organizations and enterprises: combatting disinformation, protecting democracy, and supporting the sustainable growth of consumer-facing brands. Check our our values & culture deck to learn more: https://tinyurl.com/4zjchwzs

Technology stack

Swayable uses Python (Numpy, Scipy, scikit-learn, Pandas, Celery, Flask), JavaScript (Vue.js, Node.js), MongoDB, and GraphQL.

About the role

Swayable is seeking a Senior Engineer blending Python software development expertise with scientific computing, machine learning, and AI experience to advance the state of the art analytics engine that powers our core product. In this role, you will be part of the team that productizes all AI, machine learning, and data analysis at Swayable. You will be responsible for building, maintaining, and continuously improving our tools, techniques, and architecture for high-performance computing. You will work with a talented and diverse team of engineers, data scientists, and research staff to build new features and solve novel problems across the spectrum of software engineering, data visualization, and science.

Requirements

• You have 5+ years of professional experience building scientific or quantitative data-intensive software.
• You have expertise in the scientific Python stack, object oriented and test-driven development, vectorized code, and machine learning.
• You have excellent problem solving skills and attention to detail.
• You have expertise in architecting, maintaining, and optimizing distributed, parallel computing systems.
• You keep up with the constantly evolving toolset for ML and AI Ops.
• You are knowledgeable about software architecture and can design scalable, performant solutions.
• You value code quality and write maintainable, testable code.

Preferred qualifications

• You have an advanced degree (MSc or Ph.D.) in STEM.
• You have a thorough knowledge of the Linux operating system.
• You have experience with Celery, and MongoDB.
• You believe in the scientific method and use data to drive decisions.
• You can give and receive informed, actionable feedback on technical and non-technical skills.
• You are experienced at mentoring junior engineers.
• You are a strong communicator, especially in text. You can write documentation and discuss the tradeoffs of different implementations.

Salary range: $175k-$250k

About Synaptrix Labs Inc.

Synaptrix is on a mission to revolutionize brain-computer interfaces through non-invasive approaches. We believe that the power to diagnose and treat neurological conditions safely, and to expand human potential, will become a reality with the right fusion of deep learning, signal processing, and computational neuroscience.

We're seeking a full time Research Scientist, Artificial Intelligence (PhD) to join our growing team of researchers & engineers. If you’re passionate about shaping the future of brain-computer interfaces and excited by the potential of deep learning in neurotechnology, we want to hear from you!

Responsibilities:

• Design, prototype, and optimize state-of-the-art AI systems for neural decoding, including diffusion models, graph neural networks, contrastive/self-supervised frameworks, and transformer-based sequence models.
• Conduct foundational research on neural time-series representation learning: build architectures that extract latent dynamics from EEG, EMG, or related biosignals.
• Develop high-fidelity simulation environments for testing decoding algorithms, incorporating stochastic signal noise and realistic biophysical constraints.
• Scale model training across multi-GPU and multi-node clusters using PyTorch Distributed, DeepSpeed, or JAX/Flax; profile and tune system performance for sub-10 ms inference latency.
• Build and maintain end-to-end research pipelines for large-scale signal datasets, including preprocessing, artifact rejection, and multimodal fusion with video, audio, and IMU data.
• Collaborate with neuroscientists and hardware engineers to integrate learned models into real-time BCI control loops and embedded systems.
• Contribute to core ML infrastructure: experiment tracking, model versioning, dataset lineage, and reproducibility standards.
• Publish at top-tier ML or neurotech venues (NeurIPS, ICLR, Nature Neuro, EMBC) and present findings to the research community.

Minimum Qualifications:

• PhD or equivalent deep technical expertise in Machine Learning, Artificial Intelligence, Computer Science, Computational Neuroscience, or related fields.
• Strong command of PyTorch or JAX, with experience implementing custom training loops, loss functions, and model architectures.
• Proven ability to conduct end-to-end research, from conceptual design to reproducible experiments and evaluation.
• Strong mathematical foundations in linear algebra, probability, optimization, and information theory.
• Experience working with high-dimensional time-series or sensory data (EEG, speech, video, motion capture, etc.).
• Skilled in Python, NumPy, Pandas, and scientific computing workflows; experience with CUDA or low-level GPU debugging is highly valued.
• Demonstrated ability to operate independently on open-ended problems and drive original research with limited supervision.

Preferred Qualifications:

• Deep familiarity with neural signal modeling, neural decoding, or biosignal preprocessing (EEG/MEG/ECoG/EMG).
• Experience designing self-supervised or generative models (diffusion, VAEs, contrastive, masked modeling) for noisy, non-stationary data.
• Background in reinforcement learning, optimal control, or human-in-the-loop systems, especially in continuous domains.
• Publications or preprints in top venues (NeurIPS, ICML, ICLR, CVPR, EMBC, Nature Neuro).
• Familiarity with distributed training, mixed-precision, multi-GPU orchestration, and cloud ML infrastructure (AWS/GCP/Azure).
• Contributions to open-source ML frameworks or custom CUDA kernels.
• Understanding of neural signal acquisition hardware, embedded inference, or edge ML deployment.
• Track record of curiosity-driven, independent research resulting in practical systems or open-source codebases.

About our Culture:

At Synaptrix Labs, we celebrate curiosity, open collaboration, and scientific rigor. Our interdisciplinary team spans neuroscience, AI, and clinical research, and we are united by the belief that non-invasive BCI is the key to unlocking a new era in healthcare, accessibility, and human augmentation.

Expected Compensation:

The base salary for this role is anticipated to fall within the following range. Actual compensation will depend on your experience, technical expertise, and relevant education or training. In addition to base pay, Synaptrix offers equity to all full-time employees, reflecting our commitment to shared success and long-term company growth.

Base Salary Range:

$85,000 - $150,000 USD

What We Offer:

• An opportunity to change the world and work with some of the smartest and most talented experts from different fields
• Growth potential; we rapidly advance team members who have an outsized impact
• Paid holidays, unlimited PTO