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.

Citi★3.9 (21k)· London

You will work with TypeScript, React, HTML5, CSS, JavaScript (ES6+), Chromium/Electron/OpenFin, FDC3, REST/WebSocket APIs, Kafka/Solace/Tibco, and CI/CD with Jenkins. The team delivers pricing solutions and trading GUIs for Citi’s Foreign Exchange business. You will provide technical leadership, mentor junior engineers, and drive AI integration.

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.

MAREX★3.2 (6)· London

Risk Data Analyst at Marex works with the Data Platform, Power BI, and structured/unstructured datasets. The role bridges Risk and Technology, supporting data-led risk management, monitoring, and reporting across disciplines like market, credit, and operational risk.

You will work with Python, RDKit, Biopython, OpenMM, MDAnalysis, docking, virtual screening, SAR, pharmacophore, QSAR, ADMET, and protein-ligand modeling tools. You will guide, evaluate, and improve AI-driven drug discovery workflows—reviewing agent-generated optimization plans, compound prioritizations, and modeling workflows—and lead computational chemistry strategy for live drug programs.

This role involves working with Python, PyTorch, JAX, CUDA, Linux, Docker, Kubernetes, Slurm, Ray, Flyte, and Argo. The team builds ML and physics-based infrastructure for drug discovery, including simulation workflows and agent-usable scientific pipelines. Engineers improve code quality, GPU efficiency, and distributed execution while making research tools scalable and maintainable.

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.

Trayport★4.2 (5)· London

Principal Platform Engineer designs and builds infrastructure across AWS (VPC, EKS) and Azure (AKS, AKV) using Terraform, Kubernetes, and scripting in Python/Go/Bash. The role leads AI-driven operations with LLMs and agentic workflows to reduce toil on Trayport’s global trading platform.

You'll build GTM systems using HubSpot, DealHub, Gong, Clay, APIs, webhooks, Python, JS, SQL, and AI tools (ChatGPT, Claude, Copilot, Gemini, Notion AI). This role designs end-to-end systems—from lead enrichment and routing to quote-to-cash—for Monta’s EV charging platform, including prototyping AI agent workflows.

Work with TensorFlow or PyTorch, Python, and related computer vision/graphics libraries on neural network architectures (convolutional, recurrent, transformer, diffusion-based). The Visual Computing Group (VCG) researches and develops generative models for game rendering and live video streaming to advance state-of-the-art runtime efficiency, visual quality, and latency.

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.

Use Python, SQL, BM25, vector search, reranking, and RAG pipelines to evolve Kharon's Corestream risk intelligence feed—a platform surfacing entity-level insights and topic-based risk narratives, integrating graph-based outputs into semantic search and narrative generation.

Lead a team of Data Scientists and ML Engineers building AI solutions for financial markets using LLMs, Generative AI, Deep Learning, Transformers, Agentic AI, Python, PyTorch, TensorFlow, Hugging Face, LangChain, Semantic Kernel, Azure AI Foundry, AWS AI Services, and MLOps/LLMOps practices.

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.

You will build AI agents using Python, SQL, Docker, Kubernetes, AWS (RDS, EKS, S3), GitHub Actions, RAG pipelines, BM25, vector search, hybrid retrieval, and knowledge graphs. These agents interpret geopolitical and financial signals for Kharon, a company providing global security risk intelligence.

Work with Python, SQL, BM25, vector search, reranking, RAG pipelines, agentic systems, and graph-aware search. Own and evolve Corestream, Kharon’s risk intelligence feed that surfaces entity-level insights and topic-based risk narratives for global security clients.

The technical lead will work with Java/J2EE, RESTful web services, Spring Boot, microservices, cloud technologies, Docker, Kubernetes, and CI/CD pipelines. They oversee architecture, design, and development of Java/J2EE applications, lead a team of developers, and drive technical excellence and best practices.

Infosys★3.8 (17k)· London

You will architect CI/CD pipelines using the Harness platform (CI, CD, STO, Chaos Engineering, CCM, AI Agents), Kubernetes, Terraform, Helm, OPA, and cloud services. As a Harness SME, you drive DevOps transformations, migrating enterprise teams from legacy tool chains and implementing DevSecOps governance.

You'll work with Python, APIs, MCP servers, AI harnesses, agentic operating systems, and enterprise SEO/visibility toolsets. This role extends Jellyfish's live agentic delivery stack internally and helps enterprise clients build technical foundations for agent-driven search and GEO.

Lead a disputes team at Checkout.com, working with a .NET/C# back end, React/TypeScript front end, and Python for machine learning, alongside REST APIs, event-driven microservices, and SQL. The team builds tools and models to help merchants manage and win chargeback disputes at scale. You will oversee engineers across disciplines and seniority levels, driving predictable delivery and operational efficiency.

Develop novel quantum algorithms for computing topological and geometric invariants of data, implement them on Quantinuum’s quantum hardware using pytket, Guppy, or Qiskit, and optimize performance under realistic hardware constraints with error mitigation and quantum error correction. The role contributes to advancing quantum computer capabilities for data analysis in the near-fault tolerant era.

Senior Scala engineer using Scala, Python, REST APIs, Solace, Couchbase, Gradle, Jenkins, Tekton, and OpenShift to build, maintain, and support an index calculation platform for the CIS business within Citi’s Equities Technology group.

Build backend systems with Kotlin or Java, Kafka, PostgreSQL, Redis, and microservices for a crypto savings and crypto-backed lending platform. This hands-on technical lead defines architecture, remains close to the code, and leads a small team of engineers.

Use Selenium, Playwright, Postman, JMeter, Jira, SQL, Git, Jenkins, and Azure DevOps to design and execute manual and automated tests. Validate merchant onboarding, payment processing, settlements, terminal management, and Lloyds Accept application flows across web, mobile (iOS/Android), and API systems.