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:
· 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.
· Minimum of 5 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).
· Strong communication and teamwork abilities, with the ability to convey complex technical concepts to non-technical stakeholders
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