Data Scientist

 Must Have Technical/Functional Skills
 Strong hands-on experience in Exploratory Data Analysis (EDA) and Root Cause Analysis (RCA)
 Expertise in Machine Learning techniques: classification, regression, clustering, and time-series forecasting
 Proficiency in Python and SQL
 Experience with ML libraries such as Scikit-learn, XGBoost, TensorFlow, or PyTorch
 Solid foundation in statistics, probability, hypothesis testing, and experimental design
 Experience working with large-scale enterprise datasets
 
 Roles & Responsibilities
 Data Science & Analytics
 Perform EDA to identify trends, patterns, anomalies, and key business drivers in complex datasets
 Conduct RCA to diagnose operational, business, and performance issues using data-driven techniques
 Design, build, and deploy machine learning models for predictive and prescriptive analytics
 Apply statistical modeling, causal analysis, and hypothesis testing to validate insights and outcomes
 Execute feature engineering, model evaluation, and performance tuning to ensure robust solutions
 Design and analyze experiments and A/B tests to measure business impact
 Use Palantir Foundry to integrate, curate, and model structured and unstructured enterprise data
 Implement Retrieval-Augmented Generation (RAG) patterns where applicable
 Troubleshoot data quality, model behavior, and workflow issues
 Stakeholder & Delivery Engagement