Position Title
Sr. Data Scientist
Function/Group
Sales & Commercial Capabilities
Location
India
Shift Timing
11am to 8pm
Role Reports to
Manager / Sr. Manager
Remote/Hybrid/in-Office
Hybrid
About General Mills
We make food the world loves: 100 brands. In 100 countries. Across six continents. With iconic brands like Cheerios, Pillsbury, Betty Crocker, Nature Valley, and Hagen-Dazs, we've been serving up food the world loves for 155 years (and counting). Each of our brands has a unique story to tell.
How we make our food is as important as the food we make. Our values are baked into our legacy and continue to accelerate
us into the future as an innovative force for good. General Mills was founded in 1866 when Cadwallader Washburn boldly bought the largest flour mill west of the Mississippi. That pioneering spirit lives on today through our leadership team who upholds a vision of relentless innovation while being a force for good. For more details check out http://www.generalmills.com
General Mills India Center (GIC) is our global capability center in Mumbai that works as an extension of our global organization delivering business value, service excellence and growth, while standing for good for our planet and people.
With our team of 1800+ professionals, we deliver superior value across the areas of Supply chain (SC) , Digital & Technology (D&T) Innovation, Technology & Quality (ITQ), Consumer and Market Intelligence (CMI), Sales Strategy & Intelligence (SSI) , Global Shared Services (GSS) , Finance Shared Services (FSS) and Human Resources Shared Services (HRSS).For more details check out https://www.generalmills.co.in
We advocate for advancing equity and inclusion to create more equitable workplaces and a better tomorrow.
Sr Data Scientist Insights & Analytics
Key Accountabilities
- Develop innovative approaches to assist business partners in achieving objectives through analysis and modelling.
- Apply ML and AI to analytics algorithms to build inferential and predictive models allowing for scalable solutions to be deployed across the business
- Develop end-to-end business solutions from data extraction, data preparation, data mining to ML modeling and then present insights in an easy to interpret way to the business teams
- Effectively communicate the why and how of data-driven recommendations to cross-functional teams, employing storytelling techniques.
- Collaborate as a member of the team, actively engaging with and seeking feedback from other Data Scientists.
- Mentors junior data scientist in team
- Identify and develop long-term data science processes, frameworks, tools, and standards.
- Proactively identifies and addresses issues/challenges by developing effective innovative solutions independently
- Contributes to identifying opportunities for leveraging various datasets to drive business solutions
- Proactively shares knowledge and expertise
- Manage stakeholder relationships independently to drive projects
- Be able to explore and troubleshoot niche technologies and provide automation solutions.
Minimum Qualifications
- Minimum of 8-10 years of relevant experience with a bachelor's degree; or 6-8 years with a master's degree in engineering, Data Science, Applied Mathematics, Statistics, economics or related field.
- Deep expertise in advanced machine learning, statistical modeling, and time-series analysis, with the ability to select and tailor methods based on business context and data characteristics.
- Proven track record of designing, building, and optimizing large-scale forecasting systems that drive measurable business impact across categories, markets, or regions.
- Extensive hands-on experience with time-series forecasting techniques, including but not limited to Prophet, ARIMA/SARIMA, Exponential Smoothing, and hierarchical forecasting approaches.
- Strong command of regression modeling, econometrics, and causal inference, with demonstrated ability to apply these methods to identify, quantify, and explain business drivers in real-world settings.
- Advanced experience with supervised and unsupervised learning, including regression, classification, clustering, decision trees, ensemble models, and feature engineering for structured business data.
- Expert-level proficiency in Python and/or R and SQL, with a strong focus on writing production-quality, scalable, and well-documented code.
- Hands-on experience deploying analytics solutions on cloud platforms and big data ecosystems, enabling scalable, automated, and reproducible forecasting pipelines.
- Strong ability to translate complex analytical outputs into clear, actionable business insights, influencing decision-making at senior stakeholder levels and directly supporting business objectives.
- Demonstrated ownership of end-to-end analytics projects, from problem framing and data exploration to model development, validation, deployment, and performance monitoring.
- Experience building and operationalizing machine learning applications, tools, or decision-support systems, with an emphasis on robustness, interpretability, and long-term business value.
- Ability to work independently and deal with ambiguity.
- Wholesome thinking not just ML models but also business strategies and analytical products.
- Working knowledge of Agentic AI systems, including how they are designed and implemented, along with hands-on exposure to implementation and usage of Large Language Models (LLMs)/AI tools, is a plus
Preferred Qualifications/ Skills/ Job Experiences
- Develops analytic solution framework and executes them.
- Outstanding stakeholder management skills.
- Understanding/experience in the CPG industry is desirable.
- Wholesome thinking not just ML models but also business strategies and analytical products.
- Creates stakeholder-ready deliverables and presents them to stakeholders with minimal guidance.
- Experience in basic statistical analysis, modelling, clustering, and data mining techniques to identify trends and insights.
- Technical understanding of cloud platforms and the ability to utilize data from various sources such as BigQuery, flat files, and cloud storage.
- Strong number sense and ability to identify questionable data, investigate it, and address any issues.
- Exemplary organizational skills with attention to detail and accuracy.
- Familiarity with data visualization tools.
- Proficiency in writing complex SQL queries.
- ML-based smart application development (R-shiny/Flask/Streamlit etc.)
- Ability to comprehend business use cases and translate them into data science problems.
- Capability to effectively explain model output to business stakeholders and instill trust in the model.
- Effective communication and a team player.
- Curiosity despite having developed expertise
