Frame, model and ship ML solutions that move client P&L.
What you'll do
- Translate ambiguous business problems into modelable formulations
- Build, evaluate and ship classical ML and modern LLM solutions
- Design experiments and causal analyses to quantify impact
- Own model monitoring, drift detection and lifecycle in production
- Communicate insights to executive stakeholders with clarity
What you bring
- 4+ years applied data science with production deployments
- Strong Python (pandas, scikit-learn, PyTorch) and SQL
- Solid grounding in statistics, experimentation and causal inference
- Experience with at least one MLOps stack (MLflow, SageMaker, Vertex)
Nice to have
- Published research or Kaggle competition experience
- Domain depth in financial services, retail or healthcare
Send your CV and a short note about the work you're most proud of.