Description

Design and deploy machine learning models to solve complex business problems using structured and unstructured data.

Responsibilities

• Build and validate statistical, machine learning, and advanced analytics models including regression, classification, time series forecasting, and deep learning.
• Translate business requirements into analytical questions and present model outcomes to non-technical stakeholders.
• Identify GenAI use cases and implement solutions using Prompt Engineering and RAG.
• Collaborate with Data Engineering, IT, and governance teams to deploy solutions and ensure regulatory compliance.
• Manipulate structured, semi-structured, and unstructured data files using SQL, HQL, and NoSQL.

Required Skills

• 10+ years of relevant experience, with at least 6 years in data science, machine learning, or quantitative analytics.
• Master’s degree in Computer Science, Statistics, Mathematics, Operational Research, or Data Science.
• Proficiency in Python, R, and SQL.
• Experience with Data Mining and ML libraries.
• Hands-on experience with Regression, Classification (Decision Tree, Random Forest, XGBoost), Time series (ARIMA), NLP, and Graph Analytics.
• Expertise in querying and preprocessing data from JSON, XML, and delimited numeric files.
• Ability to write transparent, well-documented, and commented code.
• Knowledge of GenAI technologies, Prompt Engineering, and RAG.

Key Skills

Education

Any Graduate