Sr Data Scientist

Mandatory Skills (Core Requirements)

1. Advanced Data Science & ML Expertise – Strong hands-on experience with regression, classification, tree-based models, clustering, time series, and recommendation systems.
2. Programming & Data Handling – Proficiency in Python (pandas, NumPy, scikit-learn, PySpark) and advanced SQL for large-scale data processing.
3. LLMs & RAG Experience – Practical experience building LLM-powered solutions, prompt engineering, and retrieval-augmented generation pipelines.
4. Statistics & Experimentation – Deep understanding of hypothesis testing, causal inference, A/B testing, and evaluation metrics (ROC, AUC, precision/recall).
5. 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)

1. Data Visualization & Storytelling – Experience with tools like Tableau, Power BI, or Looker and ability to communicate insights to executives.
2. Cloud & MLOps Tools – Familiarity with platforms such as AWS, Databricks, MLflow, feature stores, and model registries.
3. Domain Knowledge (Customer Analytics) – Experience in churn, retention, lead scoring, or customer lifecycle analytics in enterprise environments.
4. Responsible AI & Explainability – Knowledge of SHAP, LIME, bias mitigation, and model governance frameworks.
5. Leadership & Business Acumen – Ability to mentor junior team members and align data science solutions with business KPIs like revenue and customer experience.