The Principal Data Scientist will deliver AI products, manage GPT/LLM model development, collaborate on requirements, and improve model performance through data analysis and strategic thinking.
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.
Top Skills
Bentoml
Cntk
Decision Trees
Evidently Ai
Great Expectation
Hypothesis Testing
Keras
Kubeflow
Mxnet
Probabilistic Graph Models
Pyspark
Python
PyTorch
R
Regression
SAS
Sci-Kit Learn
Spss
Statistical Analysis
Svm
T-Test
TensorFlow
Z-Test
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