SOLUTION ARCHITECT L2

SOLUTION ARCHITECT L2: Job Description

London

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 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 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

Mandatory Skills: Data Science .