Quantitative Analyst (Client Solutions)

PassFort; Greater London; On-site; GBP 40,000 - 60,000; Full time

Job summary

Intropic is seeking a Quantitative Analyst (Client Solutions) in London to work directly with institutional clients, translating data into actionable strategies and backtests. Youll perform Python-based analysis, develop worked examples, and communicate results clearly.

As a junior or early-career professional, you will join a team that values rigour and collaboration, gaining exposure to portfolio construction, data quality assessment, and research publication.

Qualifications

• Strong Python and Pandas skills with hands-on data science project experience.
• Solid quantitative foundation from STEM studies and experience or coursework in finance.
• Ability to learn new concepts quickly and communicate results clearly.
• Attention to detail and good judgment under time pressure.
• Interest in finance and capital markets with willingness to engage clients.

Responsibilities

• Translate client data into strategies, backtests, and signal generation for live use.
• Be the primary technical contact for quantitative clients on data quality and methodology.
• Publish research articles, data notes, and worked examples for a technical audience.
• Build reproducible Python analyses to support research and client work.
• Investigate data issues with research and engineering teams to resolve them.
• Relay client feedback to product and research teams to shape priorities.

Skills

Python

Pandas

Data science

Quantitative analysis

Education

Bachelor's or Master's in STEM

Tools

GitHub

SQL

Jupyter notebooks

Job description

Location: London, UK (Canary Wharf) · Type: Full-Time, On-site · Start: Immediate

Who We Are

Intropic is a financial information and software company operating at the cutting edge of global capital markets. We pair modern technology (elastic cloud infrastructure and agentic AI systems) with deep market expertise to build information products that the world's most sophisticated financial institutions rely on every day. Our clients include hedge funds, proprietary trading firms, index fund managers, large asset managers, sovereign wealth funds, and investment banks, who use our products to generate alpha, manage risk, and make better decisions in fast-moving markets. We're best known for our Index Rebalance Forecast products, and we're now extending that edge into several other strategies. Headquartered in London's Canary Wharf and expanding globally, we're a team that moves fast, takes real ownership, and holds itself to a high standard of rigour and integrity.

The Role

As a Quantitative Analyst (Client Solutions), you'll work directly with Intropic's systematic clients, supporting them in getting the most out of our event-driven datasets. You'll answer their questions on data quality and methodology, and produce analysis and worked examples that show how it translates into a live strategy.

You'll engage directly with quantitative desks at some of the most sophisticated firms in the world, working alongside them on problems that genuinely move the needle in their investment process. Much of the work will be focused on hands‑on analysis in Python, alongside written research and direct client engagement.

This is a junior or entry-level role, well suited to a recent graduate or early‑career professional looking to take on real responsibility from day one.

Responsibilities

• Help clients translate our data into actual strategies, working on portfolio construction, backtesting approaches, signal generation, and turning raw forecasts into something tradeable.
• Serve as a primary technical point of contact for our quantitative clients, fielding questions on data quality, methodology, coverage, and how to work with our datasets.
• Write and publish research articles, data notes, and worked examples that showcase the value in Intropic's data to a technical audience.
• Build reproducible examples and analysis in Python to support, illustrate and aid in your research process.
• Investigate and resolve data‑related issues clients raise, working with our research and engineering teams to get to the truth quickly.
• Bring client feedback back to our product and research teams to help shape their priorities.

Requirements

• Strong working proficiency in Python and particularly Pandas. Comfortable working in Jupyter notebooks, with hands‑on experience on data science projects.
• Bachelor's or Master's degree in a STEM subject from a top university (preference towards Mathematics, Physics, Engineering, Economics or Finance), with a solid quantitative foundation built through study and/or work experience.
• Genuine interest in finance and capital markets, and the ability to learn new concepts fast.
• Excellent written communication: able to explain a technical result clearly to a sophisticated audience and produce publishable research.
• Meticulous attention to detail and sound judgment when working under time pressure or with incomplete information.

Nice to Have

• Experience within quantitative finance, either through a sales, trading or a research role.
• Familiarity with index methodologies (MSCI, S&P, FTSE etc.) and passive fund mechanics.
• Active use of GitHub and version control; exposure to backtesting or research frameworks.
• Prior familiarity with SQL and navigating sprawling data sets across platforms.
• Prior experience in a client‑facing, research, data science or sales‑engineering role at a financial data or trading firm.