Director / Associate Director - Omnichannel & Commercial Pharma
New
T
Tiger Analytics Inc.Advanced Analytics Consulting
New Jersey, United StatesFull-TimeDirector
Salary not disclosed
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Job Details
- Experience
- 12–18+ years
- Required Skills
- PythonSQLMachine LearningData scienceR
Requirements
- 12–18+ years of experience in Data Science / Advanced Analytics, with strong exposure to commercial pharma.
- Proven experience in building and deploying Next Best Action (NBA) or recommendation systems.
- Strong understanding of omnichannel engagement, including CRM (e.g., Veeva), digital marketing, and field force data.
- Hands-on expertise in Python / R / SQL, and ML frameworks (scikit-learn, TensorFlow, etc.).
- Experience with cloud platforms (AWS, Azure, or GCP).
- Strong knowledge of pharma datasets such as claims, prescriptions (Rx), EMR, and patient-level data.
- Experience in customer analytics, segmentation, targeting, and campaign measurement.
- Excellent stakeholder management and client-facing experience.
- Experience with GenAI / AI-driven personalization in pharma.
- Prior consulting experience or working in a fast-paced client environment.
Responsibilities
- Lead end-to-end delivery of data science and advanced analytics solutions in the commercial pharma domain.
- Design and implement Next Best Action (NBA) models to optimize customer engagement and decision-making.
- Develop and scale omnichannel analytics frameworks, integrating data from multiple touchpoints (CRM, digital, field, marketing).
- Partner with business stakeholders (Sales, Marketing, Market Access) to translate business problems into analytical solutions.
- Drive customer segmentation, targeting, personalization, and campaign optimization strategies.
- Build predictive models (propensity, churn, response, uplift modeling) to enhance commercial performance.
- Oversee data pipelines, model deployment, and monitoring in production environments.
- Mentor and lead a team of data scientists and analysts.
- Collaborate with data engineering teams to define data architecture, data quality standards, and governance frameworks for analytics use cases.
- Ensure alignment with regulatory and compliance standards within pharma.
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