Director, Data Science
PfizerAbout the role
ROLE SUMMARY
Global Commercial Analytics (GCA) harnesses the power of data to drive robust analytical insights that inform some of Pfizer's most critical business questions. With colleagues across the globe, GCAs rigorous analytical expertise is depended on as the compass and decision support for the enterprise. Our dynamic, exciting team of subject-matter experts comes from diverse backgrounds and experiences, including market research, data science, digital analytics, finance, and consulting. As a team, we partner to turn data into meaningful insights that will have a direct impact on patient's lives and the future of Pfizer as a data-driven organization.
The Director (T/L), Data Science is accountable for delivering data science driven strategic and tactical support for multiple brands. As a strategic partner to the US Commercial team, this person will develop and implement models and data-science derived insights that drive brands’ strategic priorities. This will include driving the execution and interpretation AI/ML models, framing problems, and shaping solutions. Also, this person will help shape the brands’ strategies and tactics by interfacing closely with Data
Science Solutions team to develop bespoke AI/ML models to meet evolving needs and will also interface closely with sales-operations to drive execution.
This role is dynamic, fast-paced, highly collaborative, and covers a broad range of strategic topics that are critical to our business. The successful candidate will join GCA colleagues worldwide that are constantly supporting business transformation through their proactive thought leadership, innovative analytical capabilities, and their ability to communicate highly complex and dynamic information in new and creative ways.
ROLE RESPONSIBILITIES
Role definition and key accountabilities include, but are not limited to:
Commercial Data Science and Insights
Provide data science and insights to US Commercial teams to drive brand tactic decisions
Act as strategic partner to frame, investigate, translate complex data related models, and answer key business questions related to the identification and evaluation of Commercial brand strategies and tactics
Lead a team of Data Scientists and manage their career development.
Connect machine learning models and insights together to identify Commercial brand opportunities and tactics to execute
Guide stakeholders via compelling and persuasive story
Strengthen the Brand and Sales teams understanding of marketplace performance and opportunities by analyzing impacts of brand strategies and tactics and partnering on data product solutions.
Collaboration with other GCA and Analytics teams
Partner with GCA IIS leads to incorporate data science capabilities and insights into analytics plans and recommendations
Ensure alignment across GCA Data Science teams and Data Science Solutions teams to ensure cohesive activities with our stakeholders
Partner with other analytic functions to advance the use of novel data sources, including RWD
PROFESSIONAL CHARACTERISTICS
Analytical Thinker: Understands how to synthesize facts and information from varied data sources, both new and pre-existing, into discernable insights and perspectives; takes a problem-solving approach by connecting analytical thinking with an understanding of business drivers and how GCA can provide value to the organization
People’s Manager: Manage a team of individuals and guide them on data science problem solving and storytelling.
Data and Information Manager: Understands and uses analytical skills/tools to produce data in a clean, organized way to drive objective insights
Communicator: Can understand, translate, and distill the complex, technical findings of the data science team into commentary that facilitates effective decision making; can readily align interpersonal style with the individual needs of others
Highly Collaborative: Manages projects with and through others; shares responsibility and credit; develops self and others through teamwork
Project Manager: Articulates scope and deliverables of projects and delivers analyses within timelines
Self-Starter: Eager to take on new responsibilities and opportunities
Technical Skills
Fluent in English (written and spoken)
Strong MS Excel and PowerPoint skills
Experience with machine learning technology
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