Sr. Manager / Associate Director - Analytics Consulting
New
T
Tiger Analytics Inc.Pharmaceutical Analytics
Toronto, Ontario, CanadaFull-TimeManager
Salary not disclosed
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Job Details
- Experience
- 15+ years
- Required Skills
- SQLAgileMicrosoft Power BIProduct ManagementSnowflakeTableauData modelingDatabricks
Requirements
- 15+ years in commercial analytics, data product management, or analytics consulting within pharma/life sciences.
- Strong understanding of commercial pharmaceutical functions, including Sales, Marketing, Market Access, Patient Services, Omnichannel Engagement, and Launch Excellence.
- Experience working with industry-standard datasets such as IQVIA, Symphony Health, Komodo, MMIT, Veeva, Claims, Specialty Pharmacy, Hub, and Patient-level data.
- Experience supporting commercial analytics, field force effectiveness, customer targeting, segmentation, omnichannel measurement, forecasting, patient journey analytics, or launch readiness programs.
- Strong technical expertise in SQL.
- Experience with cloud data platforms (Snowflake, Databricks, AWS, Azure, GCP).
- Expertise in BI tools such as Power BI and Tableau within enterprise-scale analytics environments.
- Solid understanding of data product development, including data modelling, semantic layer design, KPI frameworks, and Agile delivery methodologies.
- Ability to translate business requirements into scalable analytics solutions.
- Proven experience owning product backlogs and driving roadmap execution.
- Ability to operate independently in greenfield / build-from-scratch environments.
Responsibilities
- Partner with Life Sciences stakeholders to understand business requirements and translate them into analytical solutions.
- 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.
- 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 sprint outcomes and executive visibility.
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