Senior Data Scientist Engineer

Reports to: Data Director / Executive Sponsor

Location: Remote with occasional travel to London (2 times a month)

Contract: Full-time, permanent

Base Salary: £60,000 – £75,000 dependent on location and experience + 10% bonus scheme

Why This Role Exists

Serve Legal is forging new ground: transforming operational data into market-ready products, algorithms, and insights that redefine client value. As a driver of our Innovation Labs, you will experiment, prototype, and build compelling data solutions in a startup-within-a-business environment—boldly iterating and owning proofs-of-concept that scale.

This is a position with a balance between data science and engineering. Besides exploring and analysing datasets, you will help to establish a cloud native data foundations, with a data warehouse and supporting data pipelines.

You will be expected to use AI tools where possible to help explore, analyse and transform data.

What You’ll Do

• Build Data Products & Algorithms: Prototype and refine predictive models (e.g., compliance forecasting, anomaly detection, NLP-based feedback analysis). Embed solutions into client dashboards and intelligent tools.

• Actively Participate in Innovation Labs: Lead the data science lifecycle: ideation → prototype → pilot. Use agile methods (sprints, MVPs) to deliver validated concepts collaboratively.

• Engineer the Future: Build scalable experimentation pipelines; ensure smooth handover to production systems. Research and pilot emerging technologies (GenAI, LLMs, advanced ML frameworks).

• Champion Data Innovation: Be Serve Legal’s in-house data evangelist—translating complexity into clear, client-ready insights. Influence leadership with strategic ideas for new revenue and services.

Core Skills & Mindset

• Inventor’s Mindset – thrives in ambiguity; embraces a fail-fast, learn-fast approach.

• Business-Savvy – links data outputs to real client problems and opportunities.

• Agile Operator – experienced in rapid MVP development and iteration.

• Data Storyteller – makes technical findings accessible and impactful.

• Connector – collaborates seamlessly across data, commercial, and ops teams.

Hard Skills Required

• Programming & Data Science: Python (Pandas, NumPy, scikit-learn, TensorFlow or PyTorch) – essential; R (desirable)

• Data Engineering & Cloud: Advanced SQL, ETL/ELT tools (Airflow/dbt), AWS/Azure/GCP

• Machine Learning & AI: Classification, regression, clustering, forecasting; NLP (text mining, sentiment, LLM fine-tuning); GenAI frameworks

• Analytics & Visualisation: BI tools (Power BI, Tableau, Looker), interactive dashboards, prototypes

• Productisation & Deployment: APIs/microservices, Git/GitHub, Docker (Kubernetes advantageous)

• Other: Experimental design (A/B testing), data governance, ethical AI

Experience That Helps

• 6–10+ years in data science/data engineering with tangible productisation or algorithm development.

• Proven delivery of PoCs, prototypes, or pilots with commercial utility.

• Familiarity with compliance, retail, FMCG, logistics, or consumer insight datasets is a plus.

• Prior experience in startups, R&D or innovation-first teams is advantageous.

What’s in It for You

• Leadership of a greenfield innovation function with high autonomy and tangible impact.

• A remote-first, flexible environment—balanced with in-person connection where needed.

• Access to rich, unique datasets and a culture that values curiosity and experimentation.

• Competitive compensation aligned with senior innovation roles—plus room to build a team.