Sr Data Scientist
Mandatory Skills (Core Requirements)
- Advanced Data Science & ML Expertise – Strong hands-on experience with regression, classification, tree-based models, clustering, time series, and recommendation systems.
- Programming & Data Handling – Proficiency in Python (pandas, NumPy, scikit-learn, PySpark) and advanced SQL for large-scale data processing.
- LLMs & RAG Experience – Practical experience building LLM-powered solutions, prompt engineering, and retrieval-augmented generation pipelines.
- Statistics & Experimentation – Deep understanding of hypothesis testing, causal inference, A/B testing, and evaluation metrics (ROC, AUC, precision/recall).
- End-to-End Model Deployment – Ability to take models from prototype to production, including monitoring, governance, and performance tracking.
Secondary Skills (Nice-to-Have / Enhancing Skills)
- Data Visualization & Storytelling – Experience with tools like Tableau, Power BI, or Looker and ability to communicate insights to executives.
- Cloud & MLOps Tools – Familiarity with platforms such as AWS, Databricks, MLflow, feature stores, and model registries.
- Domain Knowledge (Customer Analytics) – Experience in churn, retention, lead scoring, or customer lifecycle analytics in enterprise environments.
- Responsible AI & Explainability – Knowledge of SHAP, LIME, bias mitigation, and model governance frameworks.
- Leadership & Business Acumen – Ability to mentor junior team members and align data science solutions with business KPIs like revenue and customer experience.