Assoc Dir , Data Science

Job Description

Associate Director Data Science, BIA Vaccines, US

The Associate Director Data Science  BIA Vaccines will be responsible for developing and communicating data-driven and actionable insights that drive greater customer and market understanding to inform launch brand strategies, help meet in-line brand growth and commercial objectives.

This hybrid role requires the individual to be an independent contributor as well as be a lead partner in helping to scope, design, and deliver well-defined advanced analytics solutions aligned to business priorities, including leading solutions that are aligned to the DHH top programs   The ideal candidate will lead a cross functional insights team that spans data science, market research, data strategy, and measurement.

The preferred candidate should have intellectual curiosity, entrepreneurial spirit, consultative mindset, strong understanding of healthcare & pharma marketing.  The person should be able to identify the data, analytics and research needs to define, enable, and inform commercial strategies of our brand and business leaders. This role will require interfacing and collaborating with many teams. The candidate should demonstrate consistently strong leadership skills.  The person will have a growth mindset and embody a culture of continuous learning. Effective communication skills are essential for a candidate to be successful in this role.

Colleagues who will thrive in this role are motivated by developing a deep appreciation of pharma secondary data sources and possess an ability to define and translate objectives and business questions into analytical problems that require advanced and scalable solutions that produce actionable insights.

Primary Job Function and Key Responsibilities

• Thoroughly appreciate the assigned internal stakeholder business needs and priorities to help build analyses promoting business objectives by delivering actionable insights

• Mine and analyze data leveraging advanced analytical/statistical techniques from disparate databases/sources (claims data/EMR Data and other sources) to drive optimization and improvement of therapy area commercial business strategies

• Be accountable for ensuring delivery of analyses with high quality standards, timeliness, compliance, and excellent user experience (routinely keep client base updated on progress)

• Establish and manages the continued close relationship with marketing stakeholders

• Comprehend the complexity/dependencies between multiple teams, platforms (people, technologies)

• Convey intensively with other platform/competencies to comprehend new trends/ methodologies being implemented/considered within the company ecosystem and bring new ideas forward that will enhance analytic capabilities of the organization

• Contribute to innovative experiments, specifically to idea generation, idea incubation and/or experimentation, identifying tangible and measurable criteria

• Where applicable, partner throughout the organization to identify, work with and direct the sourcing of externally available data sources based on the business needs, and execution of specific business objectives

• Effectively convey and positively influence stakeholders

Minimum required education:

A minimum of BS (or equivalent) in Data Science, Computer Science, Management Information Systems, IT, or an equivalent scientific/commercial discipline.  MBA or Master’s or Doctorate degree in Decision Science, Marketing, Engineering, Public Health, Biological Sciences, Nursing, Pharmacy, Mathematics, Economy, Statistics, Computer Science, Medical Sciences is preferred.

Knowledge | Skills

• Work objectively and as a Team member with Integrity | Precision | Accomplishment | Motivational Ambition | Respect

• Minimum of 3 plus years of relevant knowledge using data science to deliver measurable impact in commercial pharma landscape.

• Knowledge in mining medical claims, consumer data with a strategic/inquisitive mindset and proven record of being able to produce actionable business insights that drive positive commercial results

• Well versed with machine learning algorithms like decision tree, random forest, regression, xgboost etc.

• Experience in digital marketing, aware of KPI and measures of digital marketing

• Providing actionable insights through analytics to commercial franchises brands at various stages of product life cycle (development, launch, maturity, end of life cycle)

• Provide guidance, help define tactics and strategies to implement targeting and segmentation scheme using predictive and machine