Lead Data Scientist - Remote
Hire Resolve
Stop applying one at a time.
JobAlertsZA auto-applies to South African jobs like this one for you, overnight. Upload your CV once — we do the applying.
Start free — we apply for you →Job Description
- A company that operates a privacy-preserving data collaboration platform that lets different companies share consumer insights without ever exposing or trading actual customer data is seeking a Lead Data Scientist who will be second-in-command to the Head of Data Science, combining senior technical leadership with hands-on delivery.
Responsibilities
- Technical Leadership: Act as deputy to the Head of Data Science; mentor team members, support delivery management, and potentially lead an Agile delivery squad.
- Roadmap & Strategy: Own and prioritize the analytical roadmap, establishing reusable assets and a coherent customer analytics journey.
- End-to-End Analytics: Translate ambiguous business needs into decision-ready insights; present findings to senior stakeholders and defend evidence-based conclusions.
- Production Engineering: Write maintainable, testable, production-grade Python using modern engineering best practices.
- Data Lakehouse Architecture: Apply best practices around data grain, provenance, reconciliation, and traceability across Delta Lake and Synapse environments.
- AI-Augmented Workflows: Leverage Claude Code and agentic AI workflows across prototyping, coding, testing, and documentation.
- Multi-Party Analytics: Derive accurate insights from matched, aggregated, or imperfect datasets using weighted binning, dependency measures, and strict validation controls.
Minimum Requirements
- Experience: 7+ years in Data Science/Analytics/Data Warehousing with substantial recent DS experience + 2+ years in technical/engineering leadership.
- Education: Bachelor's degree in a STEM discipline or equivalent experience.
- Machine Learning & AI: Senior-level expertise designing, deploying, monitoring, and retraining production ML/AI models.
- Core Python Stack: Advanced Python, Jupyter, pandas, NumPy, scikit-learn.
- Data Engineering & Lakehouse: Delta Lake or similar, PySpark, feature stores, data versioning, Azure Synapse, T-SQL/ANSI SQL.
- Analytics & BI: Power BI and Python visualization tools.
- Communication: Excellent written and verbal English with strong stakeholder management skills.
Desirable Experience
- PySpark & distributed data processing
- FastAPI & Kubernetes-based model serving
- Automated testing with PyTest
- Apache Ranger or data governance frameworks
- C#.NET, Angular, or Electron development