WPP Media★4.0 (1)· London

This Senior Data Engineer role builds scalable data pipelines and infrastructure using GCP (BigQuery, Cloud Storage), Snowflake, SQL, DBT, and Python, and supports Power BI integrations. The team delivers data foundations for analytics products at WPP Media, WPP's AI-driven media operating unit, enabling creative personalisation at scale.

The role involves Excel, data visualisation, forecasting, scenario analysis, market data analysis, and AI tools (Python a plus). The analyst will join TBI’s Geopolitics Team, covering the Americas and briefing senior leaders and corporate clients on geopolitical developments. The global institute advises governments on strategy, policy, and delivery.

The role involves data visualisation, forecasting, scenario analysis, market data analysis, Excel and AI tools. The Geopolitics Team provides decision-relevant geopolitical insight to senior public and corporate leaders. The analyst will focus on China and Asia-Pacific, producing briefings and analysis.

You will work with Python, FastAPI/Flask, PostgreSQL, MySQL, BigQuery, GCP and/or AWS, and IAC/CI/CD tools to build production-grade data pipelines and MLOps infrastructure. You’ll join Ki’s commercial performance insights squad to upgrade algorithm decision data to a versioned event stream and support a Monte Carlo simulation engine for an algorithmic insurance carrier. The role is in an agile, cross-functional squad.

Synapri★0.0· London

You will use Python, SQL, PySpark, NLP, GenAI, and Azure with CI/CD to build end-to-end data science solutions. As part of a customer’s Journey Insights team, you will transform structured and unstructured customer interaction data into insights and production-ready models using machine learning, NLP, and generative AI.

NiCE★3.4 (30)· London

Develop machine learning and AI solutions using Python, SQL, NLU, and NLP. Build, evaluate, and improve models and pipelines for customer operations, working with text and structured data. Implement and evaluate new techniques across the full ML lifecycle.

JMAN Group★0.0· London

You will work with Excel, PowerPoint, Tableau or Power BI, SQL, Python, or Alteryx, with a grounding in data science or AI beneficial. JMAN delivers data-driven solutions for private equity funds, including due diligence, core reporting, Data & AI advisory, and value creation. You will lead complex client workstreams end-to-end, guiding global delivery teams and developing junior consultants.

BBVA★4.1 (7.8k)· London

You will work with C++ and Python to design, develop, and enhance pricing and risk management models for interest rate, credit, and inflation derivatives. As the primary quantitative partner for London trading and structuring desks, you will define modelling frameworks and lead model governance. You will also mentor junior quants.

You will design, build, and maintain data pipelines on Google Cloud Platform using BigQuery, Cloud Storage, Snowflake, SQL, dbt, and Python. As part of WPP Media’s global team, you will support its AI-driven media operating unit by transforming complex business requirements into reliable data assets for client analytics products.

You'll work with Python, PostgreSQL, MySQL, BigQuery, FastAPI, Flask, GCP/AWS, and CI/CD pipelines. You'll join the commercial performance insights squad to build data pipelines and event streams for monitoring algorithmic insurance underwriting, including Monte Carlo simulation.

Develop ML and AI solutions using Python, SQL, and NLU, focusing on model development, data preparation, and experimentation for customer operations. The team builds production AI systems across the full ML lifecycle. NICE Ltd. provides customer experience and financial crime software to global businesses.

Lead a team of three data scientists and three ML engineers using Python, Kafka, Spark, Flink, and on-device ML to transform phone sensor data (accelerometer, GPS) into driving-behavior models for fair insurance pricing and safety. The role owns the full telematics and pricing stack, reporting to the Director of Data.

You will work with Java microservices, Spring Boot, Python, SQL, Snowflake, dbt, Airflow, LangChain, Sagemaker, and MLflow. The data science team builds ML solutions for risk-based decisioning, pricing, and operational automation in insurtech/fintech. This is a hands-on leadership role—you will lead and develop the team while setting technical standards.

Quantitative researchers will develop mathematical, statistical, and machine-learning models for systematic trading, working in Python, with C++ and SQL as desirable, alongside large-scale data analysis. The role spans full research-to-production, collaborating with portfolio managers and engineers at a global quantitative investment firm. No team size is stated.

Deloitte★3.9 (14k)· London

You will work with Python, NumPy, Pandas, scikit-learn, LangChain, Hugging Face, LlamaIndex, Azure Machine Learning, Foundry, Git, and Agile practices. The team is Deloitte’s Tax Digital Innovation AI & Data Studio, which researches, builds, and delivers analytics and AI-driven solutions for tax and legal clients.

Work with Python, SQL, JavaScript/TypeScript, NumPy, Pandas/Polars, visualization libraries, and deep learning frameworks (PyTorch, JAX, or TensorFlow) to design and deploy full-stack data-driven applications and machine learning solutions. You will be embedded with Arsenal's Men’s First Team Analysis department, building tools that directly support coaching and analysis workflows.

Develops enterprise data platforms using Python, SQL, and Databricks, building ETL/ELT pipelines and working with data lakes and lakehouse architectures.

Use Azure, Databricks, Python, PySpark, SQL and Azure Data Factory to build scalable ETL/ELT pipelines and cloud data solutions. You will design and maintain data systems for a London Market insurer’s enterprise platform, supporting smarter decisions across Underwriting, Finance and Operations.

Work with Python, SQL, SHAP, Airflow, PyFlink, BentoML, Git, Jenkins, Octopus, Docker, JIRA and MLFlow. As a Data Scientist at Zempler Bank, you develop algorithms to protect customers, widen credit access and improve financial outcomes. You implement and monitor models in production.

You will work with Python, NumPy, SciPy, simulation modelling, optimisation under uncertainty, cloud deployment, and machine learning. The team builds an AI operating system for secure environments, taking complex scientific models from prototype to production across government and commercial programmes.

SQL and Python are used to develop pricing strategies, analyse marketing and conversion funnel performance, and evaluate product expansion opportunities. The role supports a fintech unicorn that revolutionises the credit and savings landscape. Mentoring and coaching junior analysts is also part of the position, though the team’s size is unspecified.

You’ll work with QGIS, ArcGIS, GeoPandas, Rasterio, GDAL, Python, and AI-assisted development tools. As part of the ANALYTIQ team, you’ll build geospatial models, reusable scripts, data pipelines, and interactive web tools to accelerate Systemiq’s sustainability projects across energy, materials, nature, and finance.

You will use Python, SQL, and Streamlit on an AWS data platform to clean survey data, build statistical and machine learning models (including NLP), and design interactive dashboards. As a Data Scientist II on the Data Science Consulting team, you will deliver predictive analytics solutions that optimise clients’ marketing effectiveness. You will also manage client relationships and guide more junior team members.

You will work with Python, SQL, AzureML, and XGBoost. You’ll join a small, fast-paced pricing team of 6 at a large insurance company, building alternative pricing models, geospatial models, and residual models from large, messy datasets to improve pricing and customer accessibility.

Use Python, SQL, and production ML pipelines for personalization and recommendations (embeddings, ranking, collaborative filtering) on Muzz, the world's largest Muslim dating and marriage app. You'll also use AI tools, conduct A/B experiments, and work with GCP (BigQuery/VertexAI). The role includes mentoring analysts and data scientists and shaping technical standards.