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Data Scientist – Business Insights & Analytics (Marketing Consumer)

Role context and purpose

This role is part of the **Business Insights & Analytics (BI&A)**function within the Marketing Business Unit. The role is designed to support business decision-making by applying advanced analytics and statistical/predictive modeling to consumer and digital data. The successful hire will help transform heterogeneous data into actionable insights and recommendations that improve marketing effectiveness and measurement of campaign performance.

Key responsibilities

1) Advanced analytics & modeling

• Develops statistical and/or predictive models to address business questions related to marketing performance and impact on main finance KPIs
• Contributes to consumer impact measurement by supporting measurement frameworks and effectiveness analyses (e.g., KPI definitions, and interpretation of results).
• Identifies patterns and trends, connects them to business outcomes, and tests hypotheses using quantitative methods to inform recommendations and next actions.

2) Data preparation, quality, and reproducibility

• Extracts, cleans, and integrates data from multiple sources, ensuring analytical outputs are consistent, accurate, and fit for decision-making.
• Improves reproducibility and reusability of analytical work by structuring code/notebooks, applying versioning practices, and collaborating with technical/analytics partners when needed.

3) Data storytelling & stakeholder communication

• Communicates insights and recommendations to both technical and non-technical stakeholders, translating complex analyses into clear narratives that support operational and strategic decisions.
• Produces deliverables such as reports, presentations, and/or dashboards, contributing to executive-ready scorecards and performance summaries.

Skills and requirements

Minimum requirements

• Degree in a quantitative discipline (Data Science, Statistics, Mathematics, Engineering, Computer Science, Econometrics, or related fields).
• Working knowledge of analytical programming languages used for modeling (Python and/or R), including the ability to efficiently use Generative AI tools to write, debug, and optimize code and strong foundations in statistical modeling / machine learning.
• Familiarity with prompt engineering methodologies and experience using AI assistants to automate repetitive coding tasks, data cleaning workflows, or summarize technical findings.
• Ability to work with heterogeneous datasets, designing analyses with strong attention to quality and accuracy.
• Strong communication skills to translate analysis into insights and recommendations for business stakeholders.
• Good English proficiency (international working environment).

Preferred qualifications (nice to have)

• Familiarity with digital/media measurement concepts (attribution basics, funnel metrics, A/B testing principles).
• Experience (academic or project-based) with web analytics tools and data (e.g., GA4) or datasets related to user behavior and digital performance.
• Knowledge of data visualization and dashboarding tools (e.g., Power BI).
• Utilizes AI coding assistants to efficiently research, implement, and optimize advanced statistical algorithms, ensuring best-in-class methodologies are applied to marketing measurement.

Lilly is dedicated to helping individuals with disabilities to actively engage in the workforce, ensuring equal opportunities when vying for positions. If you require accommodation to submit a resume for a position at Lilly, please complete the accommodation request form (https://careers.lilly.com/us/en/workplace-accommodation) for further assistance. Please note this is for individuals to request an accommodation as part of the application process and any other correspondence will not receive a response.

Lilly does not discriminate on the basis of age, race, color, religion, gender, sexual orientation, gender identity, gender expression, national origin, protected veteran status, disability or any other legally protected status.

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