Manager, Data Science and Ai

2 weeks ago

New York, United States Pfizer Full time

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 AI-powered tools to extract actionable insights to drive US Commercial strategies and tactics.
- Support the end-to-end 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 cross-functional teams to ensure seamless integration of brand analytics insights into decision-making 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 decision-making.

**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 large-scale 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 cross-functional 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 pre-existing, into discernable insights and perspectives; takes a problem-solving 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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