Data Scientist

Looking for immediate joners or serving notice period would be preferred

Purpose of the Role

Data Scientist II

Data Scientist II

• Analyze data and generate analytical outputs to deliver insights, evaluate the hypothesis and complete root cause analysis of the business problem.
• Should have strong analytical skillset to design end to end solution leveraging the latest machine learning (ML) techniques, including data preparation, exploratory data analysis, feature engineering, model selection, model development, model evaluation, cross-validation, and deployment
• Effectively present the analytics approach and insights to a larger business audience.
• Solve business problems which involves:
• Brainstorm with clients and internal teams to define a problem
• Translate the business problem into an analytical problem
• Identify internal and external data requirements for solving the analytical problem
• Solving the analytical problem using concepts from mathematics, statistics, Artificial Intelligence and Machine learning
• Create, maintain and enhance artefacts that can help communicate the solution to clients like dashboards, power point decks, excel sheets etc.
• Mentor team and handle day to day project deliverables and timeline.

Minimum Requirements:

• Bachelor’s degree / master’s degree in engineering, quantitative field such as statistics, business analytics or equivalent past work experience

• 4-6 years

  of experience in data science, leading teams, building hands-on Analytical models
• Advanced SQL skills, excellent programming skills in Python. Strong working knowledge of Python’s numerical, data analysis, or AI frameworks.
• Hands-on experience working with regression, clustering, decision trees and related models.
• Ability to use data and metrics to back up assumptions, evaluate the hypothesis and complete root cause analysis of the business problem.
• Experience in integrating business analysis with technical solutions that involve advanced analytics solutions, demand forecasting, segmentation, churn prediction, predictive maintenance, and route optimization, etc.