Job Title :-
Manager, Lead Data Scientist
India – Chennai, India – Mumbai
ROLE SUMMARY :-
- Works closely with the senior consultant data scientists, individuals, and project teams from business lines to identify technical solutions to business problems.
- Is a Member of the R Center of Excellence (CoE), and will work closely with other technical colleagues to deliver solutions to a variety of teams who work on projects across the portfolio, including both clinical and non-clinical applications.
- Works with the Senior Lead Data Scientist to provide subject matter expertise (SME) to business lines, helping them to design robust solutions to automate business processes, as well as being a technical SME to individuals, helping them to deliver solutions using best practices and next generation methods.
- Provide technical input to business lines helping them to build reproducible scientific workflow pipelines and use analytic tools effectively and efficiently Influence internally within Pfizer to demonstrate the power of R and modern data analytic tools Influence externally through collaborative partnership and professional networking with academic, government and industry statisticians and software engineers Is a creative problem-solver & data science subject matter expert (SME) who will drive business transformation of Statistical Programming & Analysis (SPA) organization and will champion the application of innovative technologies and data science techniques to make SPA’s workplace state of the art
ROLE RESPONSIBILITIES :-
- Provide strong technical knowledge of R, R packages, Shiny Apps, Markdown reports and other associated data science and data analytics tools (e.g. Python) and ML methods to business lines across Pfizer.
- Use agile concepts to help Pfizer business lines turn problems, ideas, or concepts into working solutions.
Provide technical input within the R CoE and to other R SMEs to deliver solutions, build reusable code & R packages, Shiny applications, and data analytic pipelines.
- Work with Pfizer Digital partners to ensure that analytical resources are state of the art – ensuring that R and associated infrastructure are delivered quickly and efficiently to enable Pfizer colleagues to have access to best available tools.
- Help build an R community at Pfizer, identifying and championing good case studies, sharing best practices, and keeping R users at Pfizer up to date with latest developments
- Help develop training on R and associated tools for Pfizer colleagues.
Provide mentorship for Pfizer colleagues seconding into the R CoE – helping them to become technical leaders and future problem-solving R consultants for their own business lines.
- Represent Pfizer at external meetings such as R in Pharma, RStudio Conference and UseR and other industry wide opportunities.
- Also provide technical input to discussions around use of R and Shiny in regulatory interactions.
Collaborate to identify & define SPA-based and cross-functional initiatives to deliver solutions that align with & implementing SPA’s digital transformation strategy.
- Postgraduates or above or equivalent experience in a scientific or related business discipline required; Degree in Informatics, Computer science, Statistics, Data Science, or related business degree with equivalent experience preferred.
- 6-8 Years of total experience with Clinical data, Statistical Analysis & Reporting, and Analytics.
Prior experience supporting Clinical Research.
- Excellence in R, Shiny, markdown and associated technologies – demonstrated via external-facing repositories such as Github or CRAN.
- Experience in software development using agile principles focusing on rapid delivery and iterative refinement.
- A demonstrated ability to interpret requirements and negotiate deliverables is essential.
Works independently, requires minimal instruction.
- Ability to organize tasks, time, and priorities.
- Ability to communicate with internal & external stakeholders, locally and globally.
- Excellent verbal and written communication skills.
- Ability to lead & influence.
- Prior working experience with teams spread across different time zones & geographies
- Machine Learning model implementation is desirable.