101 to 125 of 131 Feature Engineering Jobs in England

doing Develop and deploy ML and statistical models across credit risk, affordability and pricing Own models end-to-end, including data, feature engineering, modelling, validation, deployment and monitoring Build model monitoring frameworks and performance dashboards Explore new data sources, challenger models and A/B testing to improve ...

different backgrounds Create and maintain post-trade diagnostics tools across various strategies Qualifications: A bachelor’s, master’s, or PhD in mathematics, statistics, physics, engineering, computer science or related field Experience using AI and LLM’s Passion and interest for a quant researcher role solving real-world business problems … Minimum of two years' experience in alpha generating role Experience working with large datasets, data cleaning, preprocessing, and feature engineering Experience building, validating, deploying, monitoring, and updating predictive models Excellent programming and scripting skills Experience working independently and delivering results Excellent written and oral communication skills, experience communicating ...

Fincrime - Scam Preventionat Wise • Worship St, London, UKBack to jobs1. Home2. Jobs3. UK4. Software Engineer - Fincrime - Scam Prevention—W## Software Engineer - Fincrime - Scam PreventionWise20Software Engineering, Fincrime, Scam PreventionFull-timeGBP 68,000 - GBP 87,500 - yearlyWorship St, London, UKApply Job### Job DescriptionWise is a global technology company, building the best … world's money. For everyone, everywhere. Join us as a Software Engineer in our critical Scam Prevention team. This is a high-impact engineering role with a strong product focus, dedicated to solving complex, real-world adversarial problems to directly protect our global customer base. The Scam Prevention team ...

Senior Decision Scientist Build and deploy ML and statistical models for credit risk, affordability, and pricing Own the full model lifecycle, including data, feature engineering, modelling, validation, deployment and monitoring Develop monitoring frameworks and performance dashboards Drive innovation through new data sources, challenger models and experimentation (A/ ...

Senior Decision Scientist Build and deploy ML and statistical models for credit risk, affordability, and pricing Own the full model lifecycle, including data, feature engineering, modelling, validation, deployment and monitoring Develop monitoring frameworks and performance dashboards Drive innovation through new data sources, challenger models and experimentation (A/ ...

seeking a highly motivated Quantitative Software Engineer/Quantitative Developer to join their Systematic Strategies team in London. This is a hands‐on engineering role focused on building and scaling the technology platform that underpins the firm's systematic investment strategies. Working directly alongside Quantitative Researchers, Portfolio Managers … developing the infrastructure, tooling and production systems that support the full life-cycle of systematic trading strategies. The ideal candidate will have a strong engineering mindset, a deep understanding of quantitative research workflows, and experience building robust, scalable systems used in systematic trading environments. This role offers the opportunity ...

your results will be measured objectively via A/B testing, directly impacting our business results. We collaborate closely with the analytics, product, and engineering teams. In this role, you will: Develop, implement, and optimize machine learning models that power data‐driven features and products, from problem framing through … analysts to translate ambiguous business problems into well‐scoped ML solutions, including data requirements, modeling approach, and success metrics. Apply strong data modeling, feature engineering, and model selection skills across multiple domains, ensuring models are robust, explainable, and performant at scale. Safely integrate and operate AI/ ...

Frontend (BFF) layers, and core Java backend services; proficiency across all areas is expected, with skill distribution balanced across the team. Key Responsibilities Feature Engineering: Design and enhance user-facing features on web and mobile applications using modern frontend platforms alongside Agentic AI techniques, leveraging tools like Claude … ceremonies, address technical debt, and collaborate within multi-team setups to meet project milestones efficiently. Qualifications & Requirements Bachelor's degree in Computer Science, Software Engineering, a related technical discipline, or equivalent practical background (e.g., reputable coding bootcamp completion). 3+ years of professional full-stack, frontend, or backend development ...

lifetime value Use experimentation, analytics and owner feedback to drive decision-making Improve service delivery across Forge platforms, integrations and ecosystems Partner with Product, Engineering, Data Science, Commercial and Customer Success teams Identify opportunities to create scalable, revenue-generating managed services Monitor service quality, adoption and owner experience performance … expertise Experience building and scaling service-based, marketplace or B2B2C products Strong commercial acumen and data-driven decision-making skills Experience working closely with Engineering, Data and cross-functional teams Excellent stakeholder management, communication and influencing skills Understanding of APIs, integrations and service-based architectures Experience using AI-powered ...

procurement. We are seeking an experienced data scientist to develop forecast models for energy, metals, and other inputs, owning the full modelling lifecycle from feature engineering to deployment. You will integrate diverse data sources and translate probabilistic forecasts into procurement decisions, collaborating closely with our engineering team ...

side with experienced researchers who arecommitted to teaching, guiding, and supporting ournewest hires, learning how we think aboutexperiment design, dataset generation, time seriesanalysis, feature engineering, and model buildingfor financial datasets. At Jane Street, our researchers, engineers, andtraders sit a few feet away from each other andwork together … like to learn more, you can read aboutour interview process and meet some of the team onour website. Computer Science, Data, AI,Engineering & Technology,Life and Health Sciences, Medicine,Natural Sciences & Mathematics Enterpreneurs wanted! TUM support for prospective startups. Practicalities regarding jobmarket regulations for international students. #J-18808-Ljbffr ...

Category: Non-life Actuarial Type: Permanent Key Responsibilities (including but not limited to): Own the end-to-end modelling lifecycle: problem framing, data build, feature engineering, model development, validation, documentation Build and maintain risk and price models using GLMs and machine learning Translate models into implementable rating structures ...

working closely with Reserving and Claims Analytics teams. Own documentation and governance for model approval ahead of deployment. Test new data sources, factors and feature engineering to continually improve model predictiveness. Present model performance against agreed KPIs to key stakeholders. Mentor junior analysts, embedding best practice across ...

scoring and portfolio valuation models. You will design and maintain real-time PD models, calibrate frameworks, and ensure regulatory fairness while exploring LLM-based feature engineering. You will collaborate with cross-functional teams, mentor juniors, and contribute to long-term modeling vision, leveraging Python, SQL, XGBoost, and MLFlow ...

build the core intelligence engine for its vulnerability correlation platform in London. This hands-on role focuses on deterministic data pipelines, entity resolution, feature engineering, and scalable architectures. You will balance pragmatic engineering with strategic product sense, deciding what to build in-house versus reuse, integrating semantic ...

domains involving high-frequency or large-scale time-series data. You will focus on developing alpha signal generation pipelines from data ingestion and feature engineering to model training and deployment - in collaboration with our trading and infrastructure teams. Responsibilities: Develop ML-based alpha generation models using high-frequency … order book and market microstructure data. Design and maintain data pipelines, preprocessing, and feature extraction workflows tailored to streaming tick data. Research and implement advanced deep learning architectures for short-horizon forecasting and signal extraction. Collaborate with quant researchers and developers to integrate models into live trading environments. Optimise ...

vulnerability correlation platform. This isn't about wrapping LLMs around existing tools - it's about architecting a hybrid system where deterministic logic (entity resolution, feature engineering, hard deduplication) provides the scaffolding and LLMs add semantic reasoning on top. You'll work directly with the founder to translate security … deduplication before touching LLMs, building evaluation harnesses before declaring victory, understanding why RAG isn't always the answer for structured knowledge. This is about engineering discipline and pragmatism over hype. Experience at companies dealing with similar challenges is valuable-noisy data that needs aggregation, context building from disparate sources ...

data to trading infrastructure, where speed and reliability are fundamental requirements Building integrated environments where quantitative researchers develop, test, and deploy predictive models - from feature engineering through execution Architecting cloud-based simulation and experimentation platforms that support large-scale quantitative research without becoming a bottleneck Standing up toolchains … need to understand how data, models, and trading systems interact. You can work productively with quants and understand what they need from the engineering side. You are senior enough to take ownership. CTO wants people he can hand large initiatives to and trust the output. 6 to 15+ years ...

periods of days to weeks. Role: Quantitative Researcher for Alpha Gen (Cross-Asset). Responsible for full lifecycle research from data curation/validation, feature engineering, model development and signal generation. Role is sitting in a central research team responsible for bridging the gap between systematic and discretionary ...

build models, strategies and systems that price and trade financial instruments. You'll apply your experience in experiment design, dataset generation, time series analysis, feature engineering and model building to financial datasets, while collaborating with colleagues who will challenge and refine your approach. At Jane Street, our researchers ...

leading systematic hedge fund looking for a Quant Developer to join a front-office systematic trading team . This is a hands-on engineering role working directly with Quant Researchers and Strategists to build and support the technology behind live systematic trading strategies in production. Please note: Experience building … production systematic trading strategies is mandatory . What you'll work on: Real-time market data and tick-data processing systems Alpha generation and feature engineering pipelines ML infrastructure and research-to-production frameworks Strategy execution platforms and OMS integrations Requirements: Current experience at a systematic hedge fund ...

quantitative researchers to build models, strategies, and systems for pricing and trading financial instruments. You will apply experiment design, dataset generation, time series analysis, feature engineering, and model building to financial data, while collaborating with colleagues across research, engineering, and trading. You should be inherently curious, capable ...

these connect to our users’ financial wellbeing through the product experience Advanced Python and SQL skills, and a strong understanding of dbt and Analytics Engineering for feature engineering. In-depth knowledge of varied statistical and machine learning techniques. You're capable across the full model lifecycle, including ...

solution t esting the outputs by querying the data whilst identifying questions to further clarify. Applicants must be experts in SQL and SQL feature engineering on Google Cloud Platform (GCP)/Household 360, with familiarity in windowed functions, nested queries, query optimisation and complex ETL/ELT patterns. ...

experienced researchers who are committed to teaching, guiding, and supporting new hires, learning how we think about experiment design, dataset generation, time series analysis, feature engineering, and model building for financial datasets. #J-18808-Ljbffr ...