Data Scientist Lead

**SUMMARY OF THE ROLE**:
This position aims to provide senior leadership with data-driven insights that enhance commercial strategy, sales forecasting, marketing campaign effectiveness, and customer targeting in the pharmaceutical industry. The role focuses on integrating advanced analytics and AI into the commercial functions of Ipsen to improve overall business performance and decision-making.

**MAIN RESPONSIBILITIES**:
**Key Responsibilities**:

- Commercial Data Strategy: Lead data-driven initiatives within the commercial function, using AI and machine learning to optimize sales forecasts,
- AI Integration: Leverage machine learning algorithms to enhance commercial decision-making, such as segmentation, targeting, sales optimization, and personalization of marketing campaigns.
- Cross-Functional Collaboration: Partner with sales, marketing, and business intelligence teams to align on key business objectives and ensure analytics support business decisions effectively.
- Reporting & Visualization: Create clear, actionable reports and visualizations for senior leadership, providing insights that drive strategic commercial decisions.
- Data Governance & Compliance: Ensure all data and analytics comply with industry regulations and corporate data governance standards, including privacy and security compliance in the commercial context.

**REQUIRED SKILLS & QUALIFICATIONS**:

- Commercial Pharma Expertise: Strong understanding of the pharmaceutical commercial environment, including sales, marketing,
- Advanced Analytics & AI Skills: Expertise in advanced data analytics, machine learning, and AI techniques. Experience with predictive modeling, segmentation, and customer analytics for commercial functions.
- Technical Proficiency: Advanced proficiency in SQL, Databricks, AWS, and Python or for data analysis, modeling, and machine learning.
- Sales & Marketing Analytics: Experience in analyzing commercial data to support sales forecasting, marketing effectiveness, customer segmentation, and targeting strategies.
- Reporting & Visualization: Strong skills in creating insightful reports and visualizations that translate complex commercial data into actionable insights for non-technical business stakeholders (e.g., senior leadership).
- Business Acumen & Collaboration: Ability to translate commercial business needs into data solutions, and collaborate effectively with sales, marketing, and market access teams.
- Problem Solving: Strong analytical and problem-solving abilities to tackle complex commercial challenges and identify data-driven solutions.

**Preferred Skills**:

- Familiarity with pharmaceutical sales and marketing data, including customer relationship management (CRM) platforms, sales performance data, and marketing campaign results.
- Experience with commercial data visualization tools (e.g, Power BI) for creating dashboards and reporting.
- Knowledge of market access analytics and competitive intelligence in the pharmaceutical industry.
- Familiarity with Agile methodologies for project management.

**Knowledge & Experience**:

- Lead the development and implementation of advanced analytics and machine learning solutions to optimize sales, marketing, and commercial operations within the pharmaceutical sector
- Drive data-driven strategies for sales forecasting, customer segmentation, resulting in increased targeting accuracy and marketing
- Collaborate with cross-functional teams, including sales, marketing, and business intelligence, to translate complex commercial needs into actionable data solutions.
- Implement AI algorithms and predictive models to enhance decision-making and drive operational efficiencies in the commercial landscape.
- Manage the end-to-end analytics process, from data collection and cleaning to visualization and reporting, ensuring clarity for senior leadership and non-technical stakeholders.
- Maintain compliance with industry regulations and internal data governance standards, ensuring data privacy and security.
- Maintain existing data models with challenge and enhancements approach

**Education / Certifications**:

- Required: Master’s or PhD in Data Science, Computer Science, Business Analytics, Pharmaceutical Sciences, Statistics, or a related field, Engineer

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