- Delivers machine learning and up-to-date AI including generative AI where relevant solutions end to end from problem framing to production deployment partnering closely with product data engineering and business teams
Key Responsibilities:
- Translate business needs into ML AI problem statements and measurable success metrics
- Develop ML models and where relevant GenAI components e
- g
- retrieval augmented generation prompt pipelines with clear evaluation criteria
- Run evaluation offline metrics error analysis bias checks and monitoring baselines document decisions and assumptions
- Communicate results and limitations clearly to technical and non technical stakeholders support adoption in workflows
Technical Requirements:
- Experience 4 6 years delivering end to end data science projects
- Education Master s or PhD in Data Science Machine Learning Statistics Computer Science Applied Mathematics or related quantitative field required from this level onward
- Core stack Python Spark Git ML frameworks Databricks MLflow or equivalent cloud basics
Additional Responsibilities:
- Python pandas numpy Git for reproducible development
- Databricks Notebooks Workflows for development and orchestration
- ML flow experiments tracking model registry for lifecycle management
- Azure cloud services where relevant Azure OpenAI and Azure AI Foundry for GenAI build evaluation
- Databricks Mosaic AI including Mosaic AI Model Serving for GenAI delivery in the lakehouse
- Databricks Vector Search for RAG retrieval patterns
- Unity Catalog for governed data and model access where applicable
- Lakehouse Monitoring model monitoring for quality and drift where applicable