Data Scientist (Secondment)

Summery:We are seeking an experienced Data Scientist on asecondment engagement with a top-tier enterprise client.

In this role, you will bridge the gap between advanced machine learning and real-world business impact. You will design, build, and deploy production-grade ML models while building robust MLOps pipelines for ongoing model monitoring and lifecycle management.

Responsibilities:

• End-to-End ML Development: Propose, design, and optimize machine learning models (e.g., XGBoost, Deep Neural Networks) grounded in mathematical rigor.
• Production Deployment & MLOps: Partner with IT engineering teams to deploy models to production and create repeatable pipelines for evaluation, performance drift detection, and monitoring.
• Software Engineering Standards: Deliver clean, maintainable, production-grade code adhering to best practices like unit testing (pytest), code reviews, and structured repos.
• Business & Stakeholder Engagement: Collaborate directly with business teams to translate unstructured business questions into scalable technical solutions and actionable insights.

Requirements:

• Experience: Minimum 4+ years of solid hands-on data science experience, with a proven track record of deploying ML models into production environments.
• Education: Degree (or equivalent) in Computer Science, Econometrics, Mathematics, Operations Research, Statistics, or a related quantitative field.
• Technical Stack:
  • Expert-level skills in Python, PySpark, and SQL.
  • Hands-on experience with testing frameworks like pytest.
  • High proficiency in cloud environments—Azure Cloud Stack and Azure Databricks strongly preferred.
• MLOps & Engineering Practices: Strong background in MLOps (model versioning, experiment tracking, CI/CD, drift detection) and Git-based code reviews/pull requests.
• Soft Skills: Excellent presentation and communication skills, with a demonstrated ability to translate complex mathematical and technical concepts for both technical and non-technical stakeholders. Experience in Agile environments (Jira) is a plus.