Associate Data Scientist

Job Objective: Design, Develop, Deploy and Maintain - Predictive models based on Business Case. Handle end to end projects in Marketing Analytics for Life Science companies

Roles Responsibilities:

• Work with internal business teams to understand problem statement, requirements and use cases

• Work on Business problems including Marketing Effectiveness, Sales Engagement Next Best Action, Demand Planning, Customer Segmentation, Test Control analysis

• Conduct simple and advanced data analysis to help clients make good business decisions

• Apply advanced statistical, econometric, optimization models and algorithms to real-world business problems

• Explore emerging statistical models as well as provide analysis using existing models

• Build solutions on Structured as well as Un-structured data like Text, Images etc.

• Maintain the highest standards to follow the best practices and trending analytics in pharma domain

• Work with project leadership to define project scope

Requirements:

• Masters in Statistics, Marketing, Finance, Operations research

• 2-3 years of work experience on analytic work (use of advanced modelling projects and tools such as R, Python etc.). Knowledge of promotional channels and digital analytics.

• Strong analytical skills, excellent communication skills and the ability to communicate actionable analytical findings. Familiarity with the application of analytics to sales, marketing, or managed markets problems.

• Ability and desire to work in a proactive, highly engaging, high-pressure, client service environment.

• Should have sound experience in data mining and data analysis.

Additional Skills:

• Knowledge on various commonly used transactional data assets and others including Volumes/ Value, Rx, Specialty level, Longitudinal Patient level data assets

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.