Why This Role Stands Out
This hybrid role offers significant career growth by allowing you to lead client relationships and technical delivery, blending deep engineering skills with client-facing problem-solving. You'll thrive if you possess strong Python, data engineering, and cloud deployment expertise, coupled with the maturity to translate complex needs into actionable solutions. Apply now to elevate your impact and develop your leadership capabilities.
Quick Overview
Seniority
Mid Senior
Work mode
Hybrid
Location
london, london, United Kingdom
Job Description
Job Description
- We've had strong results with a profile that blends hands-on software/data engineering with direct client delivery - someone who embeds with a client team, understands their commercial problem, and builds and ships the tooling to solve it. We want more of this, at a senior / lead level: someone who can own the client relationship, scope ambiguous problems independently, and guide more junior engineers, not just execute a defined spec.
- A computational scientist / forward deployed engineer who can move fluidly between data pipelines, backend logic, optimization/simulation, and client-facing dashboards - and deploy it all to production. The defining trait is the combination of genuine engineering depth with the maturity to sit in front of clients, translate evolving stakeholder needs into features, and drive delivery.
- Strong Python for data and backend work - Pandas plus optimization/scientific libraries (e.g. Pyomo, Scikit-Learn)
- Building simulation, forecasting, and KPI/analytics frameworks to model financial or operational outcomes
- Data engineering: ingestion and transformation pipelines for time-series / market data, schema design, automated validation/testing (e.g. pytest)
- Interactive dashboarding (e.g. Plotly Dash, Bokeh, or similar) for decision support
- Cloud and deployment: AWS, Docker, CI/CD across dev/QA/prod; message queues (e.g. RabbitMQ) a plus
- Databases: PostgreSQL, plus exposure to NoSQL (e.g. Cassandra) and Oracle
- Owns client relationships and runs the cadence (regular working sessions, requirements gathering, alignment)
- Scopes loosely defined problems into deliverable workstreams with minimal direction
- Can technically lead on a delivery team
- Sets engineering standards (testing, deployment hygiene, code quality)
- Working with non-technical stakeholders, problem framing mindset.
- Advanced degree in a quantitative field (statistics, analytics, computer science, engineering or similar)
- Able to collaborate across European and North American time zones
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