Experience:3-15 years | Location: Pune

Objectives of this Role:

• Collaborate with product design and engineering to develop an understanding of needs.
• Research and devise innovative statistical models for data analysis.
• Work closely with engineering to help develop the next generation AI Cloud platform.
• Communicate findings to all stakeholders.
• Keep current with technical and industry developments.

Roles and Responsibilities:

• Work as the lead data strategist, identifying and integrating new datasets that can be leveraged through our product capabilities and work closely with the engineering team to strategize and execute the development of data products.
• Execute analytical experiments methodically to help solve various problems and make a true impact across various domains and industries.
• Identify relevant data sources and sets to mine for client business needs, and collect large structured and unstructured datasets and variables.
• Devise and utilize algorithms and models to mine big data stores, perform data and error analysis to improve models, and clean and validate data for uniformity and accuracy.
• Analyze data for trends and patterns, and Interpret data with a clear objective in mind.
• Implement analytical models into production by collaborating with software developers and machine learning engineers.
• Communicate analytic solutions to stakeholders and implement improvements as needed to operational systems.

Skills and Qualifications:

• Proven experience as a Data Scientist
• Programming Skills:knowledge of statistical programming languages like R, Python, and database query languages like SQL, Hive, Pig is desirable.
• Proficiency with data mining, mathematics, and statistical analysis
• Advanced pattern recognition and predictive modeling experience
• Comfort working in a dynamic, research-oriented group with several ongoing concurrent projects
• Experience with Celery,Dash ( Good to have )
• Experience with Jupyter ( Good to have )
• Experience with AWS / EKS / ECS ( Good to have )

Compensation: It will be the best in the industry and according to the experience of the candidate and company norms.