126 to 140 of 140 Feature Engineering Jobs in London

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/… solutions for a well‐defined service or product area, including data exploration, model development, offline and online evaluation, and partnering with engineering for integration. Proficiency in at least one major programming language used for ML (such as Python) and common ML/AI frameworks and tooling for model development ...

Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis. Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. ...

Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis. Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. ...

Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis. Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. ...

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 ...

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. ...

exceptional MSc) in ML, Computer Science, or related field. Deep theoretical and practical knowledge of core ML algorithms, and comfortable experimenting with model architectures, feature engineering, and hyperparameter tuning to produce high-performance and resilient models. Proven experience taking ML models from research to live production. For more ...

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 ...

platform underpinning systematic investment strategies, working with Quant Researchers, PMs and Strategists. You will design and enhance the trading platform, develop back-testing and feature engineering tooling, build market data infrastructure for real-time and historical tick data, and productionise #J-18808-Ljbffr ...

that protect millions of customers and merchants across our platform. This is a high-impact role at the intersection of machine learning, product, and engineering, where your work will directly shape how Moniepoint detects and responds to emerging fraud threats. You are a data-driven, intellectually curious Data Scientist … translate model outputs into real-world mitigations. Experience & Background: A strong foundation in statistics with a degree in a quantitative field (Statistics, Mathematics, Engineering, Computer Science, or similar). 3+ years of experience in data science, decision science, or risk analytics within fraud, payments, or financial crime. Hands ...

llgain a better understanding of the diverse arrayof challenges we consider every day, learning howwe think about experiment design, datasetgeneration, time series analysis, featureengineering, and model building for financialdatasets. Your day-to-day project work will becomplemented by classes on the broaderfundamentals of markets and trading, lunchseminars, and activities designed … readabout our interview process, meet some of theteam, and learn more about Jane Street'sinternship program on our website. Computer Science, Data, AI,Engineering & Technology,Life and Health Sciences, Medicine,Natural Sciences & Mathematics #J-18808-Ljbffr ...