Lead Data Scientist

 

Key Requirements:

• 12+ years in data science, applied ML, or advanced analytics in enterprise environments.

• Demonstrated experience extracting meaningful signals from high-volume, high-noise telemetry or behavioural datasets.

• Proficiency in Python (pandas, scikit-learn, PySpark) and statistical modelling.

• Experience building structured, repeatable analytical frameworks, including use case scoring, feasibility assessments, or prioritisation models, not purely ad hoc analysis.

• Background in designing feedback loops or iterative learning models that improve future analytical outcomes.

• Experience assessing data quality and coverage sufficiency before committing analytical investment to a use case.

• Identifying key entity relationships, behavioural patterns, and signal clusters to be encoded in the graph.

• Comfortable operating in ambiguous, early-stage data environments where frameworks need to be built from scratch.

• Experience collaborating with process or operational teams, translating data signals into process-level insights.

• Familiarity with process mining, task mining, or workforce analytics advantageous.

• Hands-on experience in Python libraries of pm4py, e.g. Petri Net and Display.

• Hands-on Databricks experience, including notebooks, creating pipelines, and visualisations.

• Knowledge of NLP and applying it to data quality.

• Structured, documented output discipline, including scoring models, ranked inventories, and feasibility assessments suitable for senior review.

• Strong remote communication and collaboration skills with onsite UK leads and Client.

• Lead Technical solutioning of Data Science Use Cases.

Nice to Have:

• LLM, OCR, RAG based architecture