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.