Data Scientist

Adria Solutions ltd
Stretford, United Kingdom
4 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Senior
Compensation
£ 75K

Job location

Stretford, United Kingdom

Tech stack

Amazon Web Services (AWS)
Amazon Web Services (AWS)
Identity and Access Management
Python
Machine Learning
NumPy
Standard Sql
Azure
SQL Databases
Working Model 2D
Feature Engineering
Analytic Functions
Pandas
Build Management
Scikit Learn

Job description

My client is a fast-growing UK business serving thousands of customers. They are investing heavily in their data capability and are now looking to appoint a Lead Data Scientist to drive end-to-end machine learning delivery within a regulated financial environment. This is a hands-on role combining technical ownership and production-grade model deployment., As Senior Data Scientist, you will:

  • Own end-to-end ML solutions - from problem framing and feature engineering to deployment, monitoring, and governance
  • Translate business objectives into modelling strategies aligned to risk appetite and operational constraints
  • Build and deploy models using Python, SQL, and AWS (SageMaker or equivalent)
  • Partner closely with Engineering, Data, and Risk/Financial Crime teams to ensure robust, production-ready solutions
  • Establish monitoring frameworks for performance, drift, and retraining
  • Drive clear documentation, traceability, and governance appropriate for a regulated environment

This role requires someone who thinks beyond experimentation - focusing on operational impact, adoption, and long-term model performance.

Requirements

  • Proven commercial ML/Data Science delivery with measurable impact
  • Experience taking models into production and managing performance over time
  • Prior experience leading or mentoring Data Scientists
  • Strong Python (pandas, numpy, scikit-learn or similar)
  • Strong SQL (complex joins, aggregations, analytical functions)
  • Solid grounding in applied statistics, evaluation design, calibration, bias/fairness
  • Experience working closely with Engineering/Data teams in production-first environments
  • Comfortable operating within regulated industries

Desirable

  • AWS experience (S3, Athena/Glue, IAM, Lambda)
  • SageMaker or equivalent ML platform experience
  • Financial services domain knowledge (risk, fraud, affordability, payments)
  • Experience with model explainability and governance documentation

Benefits & conditions

Package & Benefits

  • Hybrid working model
  • Competitive pension
  • Additional paid leave (birthday, charity, wellbeing, life events)
  • Employee assistance programme & Virtual GP
  • Modern collaborative office environment

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