Principal Data Scientist - R01551388

Job description

**Principal Data Scientist** ### Primary Skills - **ML & GenAI Expertise** – LLMs (GPT, RAG), NLP, Deep Learning - **MLOps & Deployment** – Model lifecycle management, CI/CD, monitoring - **Data Engineering** – Scalable data pipelines, big data tools (Databricks/Spark) - **Programming** – Python, SQL, TensorFlow/PyTorch - **Leadership** – Team mentoring, AI strategy, stakeholder collaboration. - Hypothesis Testing, T-Test, Z-Test, Regression (Linear, Logistic), Python/PySpark, SAS/SPSS, Statistical analysis and computing, Probabilistic Graph Models, Great Expectation, Evidently AI, Forecasting (Exponential Smoothing, ARIMA, ARIMAX), Tools(KubeFlow, BentoML), Classification (Decision Trees, SVM), ML Frameworks (TensorFlow, PyTorch, Sci-Kit Learn, CNTK, Keras, MXNet), Distance (Hamming Distance, Euclidean Distance, Manhattan Distance), R/ R Studio ### Job requirements - **Education**: Bachelor’s or Master’s Degree in Computer Science, IT, Engineering, or related fields. - **Experience**: - Overall 12+ years of experience, including **2+ years in delivering AI-powered products**. - Minimum **2 years of dedicated Product Management experience**. - At least **1 year of experience with GPT/LLM model development** (pre-processing, feature selection, hyper-parameter tuning). - **Technical Expertise**: - Hands-on experience with **Agentic AI** and **Graph RAG** solutions. - Skilled in developing and training GPT/LLM models for applications such as chatbots, Q&A systems, and recommendation engines. - Strong background in data analysis, pre-processing, feature engineering, and model selection to deliver accurate models efficiently. - Continuous monitoring and iteration to improve model accuracy and performance based on feedback. - **Collaboration & Leadership**: - Work closely with cross-functional teams to define product requirements and develop GPT/LLM use cases. - Define and align the vision for Data/AI use cases with senior leadership for medium- and long-term goals. - **Soft Skills**: - Strong analytical, strategic thinking, problem-solving, and project management skills. - Exceptional attention to detail, ability to innovate, and address challenges at both macro and micro levels.