and highly collaborative teams structured by asset class - with plenty of opportunity to rotate, cross-train, and expand your impact across the business. Tech Environment Languages: Python (NumPy, SciPy, Pandas, scikit-learn); high-performance systems in Java/C++ Tools: Airflow, Kafka, Bitbucket, Jenkins, Grafana, Prometheus, ELK Infra: Docker, Kubernetes, OpenStack, Ansible, Terraform Data: ArcticDB – the firm's proprietary DataFrame … and execution Contribute to shared frameworks and libraries supporting systematic trading globally What You'll Bring Strong Python engineering background, solid on Linux Proficiency with data libraries (NumPy, SciPy, Pandas) and workflow automation Familiarity with financial instruments and markets Clean coding habits – agile development, CI/CD, testing, and code reviews Strong quantitative foundation in statistics, optimisation, or asset pricing More ❯
and integration testing, promoting long-term stability and maintainability. Apply SOLID principles and appropriate design patterns to ensure scalable and maintainable architecture. Work with modern technologies including SciPy, NumPy, Pandas, SQL, cloud platforms, Docker, Kubernetes, and CI/CD tools. Collaborate with cross-functional teams (data science, consultants, development) across the Netherlands, UK, and US, with a focus on time … and models. Experience in developing analytic and optimization solutions in a product environment. Valuable: Experience with marketing mix modeling, forecasting, or econometric/statistical modeling. Valuable: Familiarity with NumPy, Pandas, SQL, cloud platforms, Docker, Kubernetes, CI/CD tools. Excellent communication, teamwork, and problem-solving skills. What we offer The opportunity to shape the analytics engine that drives marketing decisions More ❯
Adjust, and other MMPs Engineer features for ML models: temporal patterns, user behaviour sequences, campaign attribution Ensure data quality through comprehensive validation, deduplication, schema checks, and defensive programming Optimise pandas/Polars pipelines for performance - we process millions of events daily Handle messy real-world data: duplicates, out-of-order events, schema drift, missing fields, null handling Infrastructure & Orchestration Build … with data scientists to productionise ML workflows and model inference Requirements The ideal candidate must have... 4-6+ years building production data pipelines with demonstrable business impact Deep pandas expertise: you've built real ETL pipelines in production, understand vectorization, memory optimization, and performance patterns Deep expertise in Python and SQL with high code quality standards (e.g. ruff, mypy More ❯
About the roleWe are excited to be hiring a new Data Scientist into our team! Lendable is the market leader in real rate risk-based pricing, offering consumers transparency and product assurance at the point of application. Data Science sits More ❯
At Wayve we're committed to creating a diverse, fair and respectful culture that is inclusive of everyone based on their unique skills and perspectives, and regardless of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship More ❯
