Manager Data Science

This Position reports to:

Principal AIML Lead

Your role and responsibilities

In this role, you will have the opportunity to deliver and implement analytics strategy in one or more functional areas in alignment with business stakeholders. We are seeking a highly skilled Senior Data Scientist with expertise in finance and manufacturing domains to join our dynamic team.

The work model for the role is #LI- Hybrid in Bangalore

• Lead cross-functional projects using advanced data modeling and analysis techniques to discover insights that will guide strategic decisions and uncover optimization opportunities.
• Build, develop, and maintain analytical models that helps key business conclusions.
• Oversee the scaling of analytics projects on cloud platforms to ensure seamless functionality and integration with business operations.
• Engage with stakeholders to know their business needs, formulate and complete end-to-end analysis that includes data gathering, inspection, ongoing scaled deliverables, and presentations.
• Implement agile methodologies in all aspects of project life cycle, ensuring timely delivery of high-quality products.- Drive the collection of new data and the refinement of existing data sources; assess the effectiveness and accuracy of new data sources and data gathering techniques.

• Masters degree in computer science, Statistics, Applied Mathematics, or related field.
• 6+ years of experience in a data science role, with a focus on analytics and data modeling in cloud environments.
• Strong problem-solving skills with an emphasis on product development.
• Experience using statistical computer languages (R, Python, SQL, etc.) to manipulate data and draw insights from large data sets.
• Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.
• Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests, and proper usage, etc.) and experience with applications.
• Experience with cloud services (AWS, Azure, GCP) and under-standing of scaling analytics projects in cloud environments.