Tiger Analytics Inc.
Pharma/ Life science
Sr.Manager/AssociateDirector-CommercialDataProduct(Pharma/Lifescience)
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“Sr. Manager/Associate Director - Commercial Data Product (Pharma/ Life science) at Tiger Analytics Inc.. Skills: Data Product Ownership, Commercial Analytics, Life Sciences Domain. Partner with Life Sciences stakeholders. Own commercial data product for kidney launch”
What You'll Achieve.
launch Commercial Data Product; metric design; stakeholder alignment; data product ownership; segmentation frameworks; KPIs; data products used by commercial leadership; scalability and reuse; self-service analytics; KPI governance; adoption tracking; success metrics for the product; clear sprint outcomes; executive visibility
Industry & Context.
What They're Looking For.
Must Have
12+ years in commercial analytics, data product management, or analytics consulting within pharma/life sciences, experience and domain knowledge in gene therapy, with exposure to relevant processes, workflows, and industry applications, experience with pharma launches, including segmentation, performance tracking, and KPI design, Hands-on understanding of Snowflake (data modeling, performance considerations), Power BI semantic layer knowledge along with visualization, Proven experience owning product backlogs and driving roadmap execution, Ability to operate independently in greenfield / build-from-scratch environments
What You'll Do.
Partner with Life Sciences stakeholders
Own commercial data product for kidney launch
Translate launch strategy into segmentation frameworks
Drive stakeholder alignment across Marketing
Own and prioritize product backlog
Partner with engineering team to design data models
Ensure Power BI semantic model understanding
Enable self-service analytics
Establish KPI governance and adoption tracking
Lead a small cross-functional pod
Operate in an agile delivery model
Act as interface between business and technical team
How You'll Work.
Team & Collaboration
Partner with Life Sciences stakeholders; Drive stakeholder alignment across Marketing, Sales, Market Access, and Analytics; Partner with the engineering team; Lead a small cross-functional pod (data engineers, analysts); Act as the primary interface between business stakeholders and the technical team
Process & Methodology
Own and prioritize the product backlog, driving roadmap execution, Operate in an agile delivery model
Full Job Description
Tiger Analytics is an advanced analytics consulting firm. We are the trusted analytics partner for several Fortune 1000 companies, enabling them to generate business value from data. Our consultants bring deep expertise in Data Science, Machine Learning and AI. Our business value and leadership has been recognized by various market research firms, including Forrester and Gartner. We are seeking a Senior Manager / Associate Director with a strong Life Sciences background and hands-on commercial analytics experience to launch Commercial Data Product to support an upcoming pharma launch. This role will lead a small, dedicated pod to design and build a Snowflake-native, Power BI–aligned data product from the ground up. The position gives an opportunity to focus on data product ownership, metric design, and stakeholder alignment. The candidate should have strong experience and domain knowledge in gene therapy, with exposure to relevant processes, workflows, and industry applications. Key Responsibilities * Partner with Life Sciences stakeholders to understand business requirements and translate them into analytical solutions * Own the end-to-end commercial data product for a kidney launch, from vision to execution. * Translate launch strategy into segmentation frameworks, KPIs, and data products used by commercial leadership. * Drive stakeholder alignment across Marketing, Sales, Market Access, and Analytics * Own and prioritize the product backlog, ensuring alignment with launch milestones. Partner with the engineering team to design Snowflake-native data models optimized for scalability and reuse. * Ensure strong Power BI semantic model understanding (measures, relationships, performance). * Enable self-service analytics through well-designed datasets—not dashboards alone. * Establish KPI governance, adoption tracking, and success metrics for the product. * Lead a small cross-functional pod (data engineers, analysts). * Operate in an agile delivery model with clear spr
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