Principal Data Scientist

Responsibilities:

• Collaborate with business stakeholders to understand and refine data-related questions and requirements
• Utilize advanced analytics to uncover hidden insights in large datasets and provide actionable recommendations.
• Design and implement data models and algorithms to support data-driven decision making.
• Investigate internal and external data sources to determine availability, quality, and relevance
• Identify, collect, and analyze relevant data needed to address specific business challenges
• Propose solutions to close data gaps.
• Define data structures, formats, and transformation logic needed to support reporting and analytics.
• Leverage data science techniques to uncover trends, patterns, and correlations in large datasets.
• Apply data science techniques to automate data validation processes and enhance data integrity.
• Conduct thorough quality assurance checks on data to ensure accuracy and reliability.
• Present findings and insights clearly to business stakeholders.
• Stay current with emerging trends and technologies in data research, business intelligence, and data science.

Skills:

• 8+ years hands-on work experience in the domain of data science & analytics (work experience in IT, software engineering, data engineering or any other areas is to be treated as extra and optional).
• Proficient in AI/ML algorithms and implementation experience with Python libraries. (Pandas, Numpy, scikit-learn, TensorFlow, Keras)
• Data mining & preparation using Python.
• Proficient in statistical analysis to drive decisions.
• Build and verify hypothesis based on abstract problem statement.
• Practical experience with Databricks for writing and deploying code through jobs and pipelines.
• Proficiency SQL (programming languages) for data science related assignments.
• Experience on building and deploying pipelines in Microsoft azure.
• Design and implement Generative AI solutions utilizing LLMs such as GPT, Claude, and LLaMA.
• Fine-tune and evaluate Large Language Models for industry-specific tasks.
• Proficiency in Python and libraries such as LangChain, Transformers, OpenAI SDK, or Hugging Face.
• Deep understanding of LLMs, prompt engineering, and transformer architectures.
• Educational background in Math / Statistics / Engineering / Science.
• Strong communication and teamwork abilities, with the ability to convey complex technical concepts to non-technical stakeholders.