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Principal Data Scientist - R01551388

12 years

0 Lacs

bengaluru karnataka india

Posted:1 week ago| Platform: Linkedin logo

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Skills Required

data ml deployment model management engineering databricks programming python sql tensorflow leadership mentoring ai strategy collaboration testing test regression pyspark sas spss analysis forecasting arima svm pytorch kit keras development processing tuning training monitoring vision macro

Work Mode

On-site

Job Type

Full Time

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.

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