Manager, Data Science and Ai - New York, United States - Pfizer

Pfizer
Pfizer
Verified Company
New York, United States

2 weeks ago

Mark Lane

Posted by:

Mark Lane

beBee recruiter
Description

We are looking for a Manager, Data Science and AI who will be responsible for delivering data-driven insights and/or AI-powered analytics tools to Pfizer's Commercial organization and will support a brand or therapeutic area.

This includes supporting implementation of AI/ML models, framing problems, and shaping solutions with clear and compelling communication of data-driven insights.

Product / Brand and Therapeutic Area (TA) Insights

  • Deliver advanced analytical models, predictive algorithms, and AIpowered tools to extract actionable insights to drive US Commercial strategies and tactics.
  • Support the endtoend delivery of data science insights, from framing the business question, designing the solution, and delivering recommendations.
  • Break down technical concepts into digestible insights and guide diverse stakeholders how to interpret.
  • Foster strong relationships with key stakeholders, effectively communicating the value proposition of data science
Collaborate Cross-Functionally as a Brand/TA Focused Analytics POD

  • Collaborate within the analytics POD, coordinating efforts with the Insight Strategy & Execution and Market Research Insights counterparts to develop and execute a comprehensive brand analytics plan.
  • Deliver consolidated insights and actionable recommendations to US Commercial teams, ensuring alignment with strategic objectives and insights findings.
  • Represent data science function and capabilities in Analytic POD meetings.
  • Work closely with crossfunctional teams to ensure seamless integration of brand analytics insights into decisionmaking processes and strategic initiatives.
Cross-Functional Collaboration

  • Work closely with Analytics Engineering to ensure the data ecosystem is conducive for data science modeling purposes.
  • Partner with Digital teams to enhance data science capabilities, aligning efforts to leverage digital data sources effectively.
  • Foster collaboration with other teams to ensure seamless integration of data science initiatives across the organization's infrastructure, promoting efficiency and effectiveness in leveraging data for informed decisionmaking.

Qualifications:


  • Minimum of bachelor's degree with 5+ years of experience, preferably in engineering, economics, statistics, computer science, or related quantitative field.
  • Advanced degree preferred with 0~2 years of experience in Applied Econometrics, Statistics, Data Mining, Machine Learning, Analytics, Mathematics, Operations Research, Industrial Engineering, or related field preferred.
  • Experience using data science models to solve problems in an education or business environment setting.
  • Experience with supporting commercial strategies and tactics, experience in pharmaceutical or healthcare industry is preferred.
Relevant Experience

  • Experience with both traditional SQL and modern NoSQL data stores including SQL, and largescale distributed systems such as Hadoop and or working in Snowflake/Databricks.
  • Experience with machine learning technology, such as: big data stack, Java, Python, R, Scala and visualization techniques, including Dash, Tableau and Angular.
  • Experience in understanding brand content, strategy, and tactics
  • Ability to effectively utilize dashboards and data products to derive insights.
  • Ability to partner with crossfunctional teams (Commercial, Medical, Operations) to execute brand tactics.
  • Able to connect, integrate and synthesize analysis and data into a meaningful 'so what' to drive concrete strategic recommendations for brand tactics.
  • Capable of describing relevant caveats in data or in a model and how they relate to business question.
  • Ability to be flexible, prioritize multiple demands and deal with ambiguity.
Competencies

  • Analytical Thinker: Understands how to synthesize facts and information from varied data sources, both new and preexisting, into discernable insights and perspectives; takes a problemsolving approach by connecting analytical thinking with an understanding of business drivers and how CAAI can provide value to the organization.
  • Data and

Information Manager:
Understands and uses analytical skills/tools to produce data in a clean, organized way to drive objective insights.

  • Communication: 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.
  • Collaborative: Manages projects with and through others; shares responsibility and credit; develops self and others through teamwork.
  • Project Manager: Clearly articulates scope and deliverables of projects; breaks complex initiatives into detailed component parts and sequences actions appropriately; develops action plans and monitors progress independently; designs success criteria and uses them to track outcomes; drives implementation of recommendations when appropriate, engages with stakeholders thro
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