Data Scientist - GenAI

• Professional Experience: 7+ years in business analysis, requirement gathering, and solution workflow design for AI/ML/Analytics projects.
• Programming Skills: Proficient in Python and SQL.
• ML Libraries and Applications: Strong understanding of ML libraries and applications (e.g., Time series analysis, Neural Networks, SVMs, boosting methods), with implementation experience in Python.
• Deep Learning Techniques: Experience with deep learning techniques.
• Communication Skills: Excellent communication skills to collaborate effectively with business SMEs and UX teams.
• DevOps Practices: Intermediate knowledge of DevOps practices, including CICD, Automation, Build Management, and Versioning.
• Cloud Services: Understanding of Cloud services, including Microsoft Azure, GCP, or AWS.
• LLM/Gen AI: Experience in LLM/Gen AI – Prompt Engineering, RAG, and parameter hyper-tuning.
• Pyspark: Experience in Pyspark is an added advantage.

RESPONSIBILITIES:

• Strong problem-solving, critical, and analytical thinking skills, with hands-on coding expertise.
• Proficient in data fetch, data merge, data wrangling, exploratory data analysis, and feature engineering.
• Python and SQL skills with practical knowledge of machine learning algorithms.
• Drive client engagement and align the development team with a technical roadmap.
• Implement analytical requirements by defining and analyzing system problems, designing, and testing standards and solutions.
• Develop solutions by preparing and evaluating alternative workflow solutions.
• Study business functions to determine operational objectives, gather information, and evaluate output requirements and formats.
• Design new analytical solutions by analyzing requirements, constructing workflow charts/diagrams, studying system capabilities, and writing specifications.
• Improve systems by studying current practices and designing modifications.
• Recommend controls by identifying problems and writing improved procedures.
• Define project requirements by identifying milestones, phases, and elements, forming a project team, and establishing the project budget.
• Monitor project progress by tracking activity, resolving issues, publishing progress reports, and recommending actions.
• Maintain system protocols by writing and updating procedures.
• Provide user references by writing and maintaining user documentation, providing help desk support, and training users.
• Maintain user confidence and protect operations by ensuring information confidentiality.
• Prepare technical reports by collecting, analyzing, and summarizing information and trends.
• Maintain professional and technical knowledge by attending educational workshops, reviewing professional publications, establishing personal networks, benchmarking state-of-the-art practices, and participating in professional societies.

Artificial Intelligence,Machine Learning,Aws