Analyst/Consultant - Products Analytics - Life Sciences Practice

Analytics

Products Analytics - Life Sciences Practice

Job Description

R&D Analytics - Life Sciences Domain, Analyst/Consultant

3-7 yrs experience

Key requirements:

- Should be familiar with Life Sciences domain and the different business units (Commercial, R&D, Supply Chain) at a high level at least

- Should have a good understanding of the Pharmaceutical R&D in particular i.e. clinical trials, data clinical trials produce, how patients/ subjects recruitment happens, how clinical trials sites are enabled, different phases, endpoints and objectives; inclusion and exclusion criteria; clinical trial data management and statistical analysis.

- Basic concepts of Pharmacovigilance reporting process and safety signal detection

- Basic understanding of FDA Adverse Event Reporting System and Eudra-vigilance datasets

Technical Skills:

- Good hands-on knowledge of Excel functions and formulae and basic data analysis tools

- Strong hands-on any RDBMS (MySQL/ SQL Server/ Oracle PLSQL) skills

- Hands-on R/Python programming skills

- Experience of any visualization tool like Tableau, Spotfire, Qlikview would be a plus

- Statistical tests and basics of predictive modeling

Roles and Responsibilities:

- Understand customer requirements on pharmacovigilance, signal detection, and other R&D business problems

- Identify challenges to implement and execute the proposed solution and communicate with the same with project lead and the customer proactively

- Figure out the data requirements and analytics solutions

- Be able to do a literature search and implement new analytics requirements from scratch to improve the existing solution

- Participate in proposals and business development efforts in the field of pharmaceutical R&D (This is more for Consultant and above- NOT necessarily for Analyst level)

- Collaborate with team members and mentor junior team members so that they can deliver independently

Educational Background

- Engineering from reputed college or equivalent with strong work experience in life sciences and statistical analysis

- Master's degree in Business Administration from a reputed college or equivalent,

- Statistics / Operations research masters from reputed college or equivalent