You'll work with Microsoft Fabric, PySpark, Python, T-SQL, DAX, Infrastructure as Code, Git, and Azure DevOps. You'll design, build, and maintain data pipelines, lakehouses, and data warehouses within Fabric to drive business intelligence and analytics.

Uses SQL, Python or scripting, BI tools like PowerBI/Looker/Tableau, spreadsheets, and Git to investigate fraud and build dashboards. The role sits in fraud analytics at Moniepoint, an all-in-one financial services platform powering POS transactions and banking across Nigeria and emerging markets.

Relay Technologies★2.0 (9)· London

At Relay Technologies you will build and own time-series forecasting models for parcel volume, inbound international volume, and parcel size/weight, using Python and ML frameworks. You will work on the Network squad’s demand-forecasting engine that predicts parcel movement across sortation, middle-mile, and last-mile operations, directly affecting cost per parcel. This is a hands-on individual-contributor role, serving as the technical anchor for Demand Forecasting, collaborating with a Senior Data Scientist, ML Engineer, and Analyst.

Work with Python, SQL, graph databases, graph ML, Docker, Kubernetes, and LLMs. Own and evolve Kharon's risk propagation engine that analyzes entities in a knowledge graph to surface risk signals for global security clients.

HarbourVest★3.1 (16)· London

This role involves productionizing Data Science and AI prototypes using Python, containerized or cloud-based delivery, Snowflake, Power BI, Git, and CI/CD pipelines. You will design analytics workflows and support legacy solutions, partnering with global teams to bridge raw data and analytics-ready assets at HarbourVest, a private markets investment firm.

MAREX★3.2 (6)· London

You will work with Power BI, alongside a Data Lakehouse architecture and a central data catalogue, to analyze and validate structured and unstructured risk data. You will act as the bridge between the Risk function and Technology to support data-led risk management, oversight, monitoring and reporting across the firm.

You use Python and supervised machine learning on tabular data to own and build production credit models that decide which small businesses iwocaPay’s B2B Buy Now Pay Later product can fund. You co-own the full credit modelling stack with one other data scientist.

You'll work with Python, SQL, PySpark, and the PyData stack to build machine learning and analytics solutions for McKinsey's clients across industries, translating business challenges into statistical models and deploying them to production. QuantumBlack, AI by McKinsey is a data science and AI consulting firm applying advanced analytics to solve complex client problems. You'll collaborate with Data Scientists, Engineers, Designers, and Product Managers globally while based in London, with exposure to R&D projects and conference presentations.

Work with Microsoft Fabric (Lakehouses, Warehouses, Dataflows, Pipelines), Azure (SQL, Data Lake, Data Factory), SQL, Python, and REST API/SFTP to build ETL/ELT solutions. You will deliver modern data integration solutions for a diverse portfolio of clients within RSM’s Global VAT Team.

Principal Data Engineer role using GCP, Python, Node.js, BigQuery SQL, and Jenkins CI/CD. The team enables Sky’s growth through Data and AI, deepening customer relationships, optimising commercial performance, and enhancing operational efficiency. The role provides technical leadership, managing Solution Architects and setting engineering standards.

Work with Python, Snowflake, Power BI, Git, CI/CD, and cloud deployment to productionize data science and AI prototypes. You will bridge raw data ingestion to analytics-ready assets, building and maintaining analytics workflows and dashboards for a global investment firm.

Use Python, SQL, graph databases, Docker, Kubernetes, and LLMs to own Kharon’s risk-propagation engine that evaluates entities in a knowledge graph and surfaces risk signals. The role spans research, data engineering, and product to evolve a production system for global security analytics.

You will own Relay’s Demand Forecasting models, working hands-on with Python, ML frameworks, and forecasting tools to predict parcel volume, weight, and size at outcode granularity out to D30. You set the technical direction for the Network squad’s forecasting engine, which drives sortation, middle-mile, last-mile, and expansion decisions. The centralised data team has ~30 people, with you acting as the senior IC anchor, mentoring a Senior Data Scientist and an Analyst.

Work with Excel, SQL, Python, R, Tableau, Power BI, and Azure AI Fundamentals. Newto Training provides a data analytics career programme with live instructor-led training, project work, and exam preparation for entry-level roles.

You will work with AWS, Python, SQL, ETL/ELT pipelines, data warehousing, and APIs. You will own the data platform for a company developing AI and machine learning products that help enterprise clients make decisions. You will start as a senior individual contributor with the opportunity to build and lead a future data team.

You’ll work with SQL, Python, Snowflake, AWS/GCP, and APIs to build and evolve the firm’s cloud-based data platform, developing scalable data pipelines and integrating data to support investment decisions. You will mentor two junior Data Engineers.

Cint★3.5 (13)· London

Use Python and SQL for statistical modeling and machine learning to optimize Cint's programmatic research marketplace (Cint Exchange). You will analyze marketplace dynamics, conduct A/B tests, and build predictive models to guide product and pricing strategy.

Goldman Sachs★3.9 (2.3k)· London

Build a high-performance, low-latency data platform for post-trade processing using Java, Kafka, Flink, SingleStore, HDFS/S3, and Scala. You will own the full lifecycle of core systems, designing distributed computation and an AI-powered UI/agent framework to deliver intelligent analytics over large-scale business data.

Hudson River Trading★4.5 (2)· London

You will use Python, C++, Pandas, NumPy, R, or MATLAB to build and maintain predictive trading models. As an algorithm developer, you research and test novel order execution and model training methods, applying

Hudson River Trading★4.5 (2)· London

You will work with Python, Pandas, NumPy, R, and MATLAB to apply statistical analysis and machine learning to vast quantities of market data. The team builds and maintains predictive trading models for the company's high-performance trading infrastructure. You will research, develop, and test order execution methods to increase trading efficiency.

Quantitative Researchers at Jane Street build models, strategies, and systems for pricing and trading financial instruments, working with Python, petabytes of data, and a large GPU cluster. They apply statistical and ML techniques, from linear models to deep learning.

Design, build and optimise ETL data pipelines using Databricks, PySpark, Python, and SQL for a leading global investment bank. You will work on large-scale enterprise data platforms in a fast-paced financial services environment.

Virtusa★3.7 (1.1k)· London

Work with Snowflake, DBT, Python, SQL, and AWS services to build enterprise data platforms. The role supports a global pharma engagement, designing scalable data solutions for advanced analytics, clinical insights, and business intelligence.

Snowflake, DBT, Python, SQL, and AWS. Leads architecture of enterprise data platforms for a global pharma engagement supporting clinical insights, business intelligence, and data governance.

Work with SQL, Python, and modern data technologies (dbt, Spark, containers, DevOps tooling, orchestration tools, Git, AI/ML). As a Solution Engineer for the UK market, you present Snowflake’s technology and vision, working hands-on with prospects to demonstrate value through demos, proof-of-concepts, and design.