26 to 31 of 31 Statistical Modelling Jobs in Central London

collaborate with cross-functional teams to design, build, and implement data science solutions that directly feed into core product offerings. This is an exciting opportunity to apply ML and statistical techniques to real-world problems, while also developing in areas such as software engineering, data pipelines, and ethical product delivery. Key Responsibilities Collaborate with product teams to identify opportunities … maintain data pipelines to support experimentation and model development Develop and deploy machine learning models in production environments Present insights and results to technical and non-technical stakeholders Apply statistical methods and model validation techniques to reach accurate conclusions Work with data engineers to ensure clean, usable datasets Contribute to ethical, privacy-aware, and user-centric data products Stay More ❯

or other adjacent OOP or multi-paradigm languages (C, C++, Java, Python etc.) Logical thinking, analytical skills and exception creative problem-solving abilities. Experience in using Excel to model statistical models, or similarly high level Excel experience. Ability to take responsibility for organizing work within a production schedule, managing files and meeting deadlines under their own initiative. Good oral More ❯

Quantitative Analyst required by a sports trading company based in central London. The company have been established for more than 10 years, successfully developing statistical models and analytical frameworks. The successful Quantitative Analyst will work within the prediction team, using extensive datasets to enhance existing predictive models as well as researching new methods. The role will be working alongside … a team of Quants, Developers, and Analysts. Due to the nature of the business this is mainly an office-based role. Experience required: 3+ years' experience within predictive modelling, machine learning, and probability theory. Ideally this would be within sports or gaming/betting industries. Understanding of techniques such as Monte Carlo simulation, Bayesian modelling, GLMs, mixed effects More ❯

The Business: This is not just another data consultancy—we're a team of curious minds using AI and statistical modelling to help organisations solve real-world problems and make smarter, faster decisions. Whether it’s uncovering insights from vast datasets or building predictive tools to shape future strategies, we believe data science should make a difference—a … Graduate to join our growing team and support the increasing demand for our analytical services. As a Data Science Graduate you’ll: Support the delivery of quantitative research and statistical analysis projects Learn and apply techniques such as conjoint analysis , MaxDiff , segmentation , and key drivers analysis Work alongside experienced data scientists and gradually take on more responsibility Deliver smaller … years of experience in data science or quantitative market research . You should: Be comfortable using and interpreting data to draw insights Have a basic understanding of key statistical techniques such as: Conjoint analysis MaxDiff Segmentation Linear or logistic regression Significance testing Be confident using Excel , PowerPoint , and Word Be open to learning tools such as: SPSS , Q , Sawtooth More ❯

the quality of insights depends on the quality of the data. 10. You understand that models are only as good as their assumptions. You can critically assess epidemiological and statistical models, ensuring biases and confounders are accounted for. You’re comfortable with methodologies like propensity score matching, inverse probability weighting, and instrumental variable approaches. 11. You don’t just … and limitations of each data source. 14. You know when a real-world study is the answer—and when it’s not. You can identify when another approach (e.g., modelling, meta-analysis, or a new trial) is needed. 15. You believe in impact, not just publications. Publishing is great, and you’ve done it—but what excites you is More ❯

that interact directly with exchanges, including automated RFQ pricing for options. Quantitative Problem-Solving: Work closely with traders to develop solutions for portfolio optimisation, large-scale data analysis, and statistical modelling. Market Structure & Trading Expertise: Apply your knowledge of market microstructure, volatility trading, options pricing, hedging, and Delta1 products (futures, ETFs, stocks, swaps). Ownership & Collaboration: Engage directly with … for building robust, high-performance trading systems. Low Latency Expertise - A strong understanding of optimizing for speed in trading environments. Quantitative Background - Hands-on experience with large data analysis, statistical techniques, and trading models. Trader-Facing Mindset - Ability to engage with the desk, understand business needs, and take ownership of algo development. Why Apply?: Work on greenfield algorithmic trading More ❯