Lead Data Scientist building GenAI - driven products and ML solutions for S&P Global. Mentoring team members and delivering high - impact projects in a global environment.
About the role
- Data Scientist developing statistical models and data-driven solutions at Mondelēz International. Collaborating with stakeholders to drive insights and optimize business operations.
Responsibilities
- Define requirements for analysis in a given business area and perform detailed analysis and identify trends defined in the requirements
- Identify patterns and help the business react to changing business conditions.
- Perform root-cause analysis and interpret data.
- Work with large amounts of data such as facts, figures, and mathematics/formulas and undertake analytical activities and delivers analysis outputs in accordance with customer needs and conforming to established standards.
- Understand and be involved with aspects of the data science process.
- Develop and implement statistical models, with a strong focus on Bayesian models and sales forecasting techniques.
- Conduct regression and causal inference analysis to understand key drivers and predict future outcomes.
- Utilize advanced Python programming skills to manipulate, analyze, and visualize large datasets.
- Collaborate with cross-functional teams (e.g., Sales, Marketing, Operations) to identify opportunities for data-driven optimization.
- Communicate complex analytical findings clearly and concisely to both technical and non-technical audiences.
- Contribute to the development of data science best practices and methodologies within the organization.
- Stay up-to-date with the latest advancements in data science and related fields.
Requirements
- Bachelor's or Master's degree in Statistics, Mathematics, Computer Science, Economics, or a related quantitative field.
- Minimum of 3-5 years of experience in a Data Science role or related analytical field.
- Advanced proficiency in Python, including experience with relevant libraries such as NumPy, Pandas, Scikit-learn, etc.
- Solid understanding of statistical concepts, probability theory, and mathematical modeling.
- Proven experience with Bayesian modeling techniques.
- Experience in sales forecasting methodologies.
- Strong understanding of regression analysis and causal inference.
- Familiarity with Machine Learning methodologies (a plus, but not critical).
- English proficiency: B2 level or higher (written and spoken).
- Excellent communication and interpersonal skills , with the ability to effectively communicate with diverse stakeholders.
- Demonstrated ability to work both independently and collaboratively in a fast-paced environment.
- Strong problem-solving skills and a passion for using data to drive business decisions.
- Bonus Points: Experience with cloud computing platforms (e.g., AWS, Azure, GCP). Experience with data visualization tools (e.g., Tableau, Power BI). Experience with A/B testing and experimental design.
Benefits
- No Relocation support available
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