General Mills

D&T Data Scientist II

India · Hybrid · Full time

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About the role

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EmployerGeneral Mills
LocationIndia
Work styleHybrid
Employment typeFull time
Employer posted24 Aug 2026

COMPANY OVERVIEW

We exist to make food the world loves. But we do more than that. Our company is a place that prioritizes being a force for good, a place to expand learning, explore new perspectives and reimagine new possibilities, every day. We look for people who want to bring their best — bold thinkers with big hearts who challenge one another and grow together. Because becoming the undisputed leader in food means surrounding ourselves with people who are hungry for what’s next.

OVERVIEW

General Mills, Digital and Technology India, is seeking a Data ScientistIIto join the Data Science team. Data Scientists within our team are dedicated tobuildenterprise intelligent automations and enable ML solutions on various use cases including but not limited to demand forecasting, text classification, operational analytics, logistics optimization, price optimization, ecommerce, and market mix modelling. They are also responsible forcuratinga community ofpracticeto determine the best standards and practices around data science at General Mills.

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KEY ACCOUNTABILITIES

Partner with Lead Data Scientists and business stakeholders to deliver value-added insights and intelligent solutions through AI and machine learning.

Develop maintainable and scalable AI solutions using established data science best practices.

Collaborate with ML and Systems Engineers to deploy models in a scalable and efficient manner, monitor production performance, and proactively address model degradation after deployment.

Build strong business and domain knowledge to understand stakeholder needs and deliver relevant, practical solutions.

Manage assigned priorities and tasks with consistency, accountability, and strong execution discipline.

Engage stakeholders to understand problem statements, clarify business needs, and drive measurable outcomes.

Contribute to discussions across the team by evaluating and comparing different approaches to solving problems.

Serve as an advocate for the data science team and the value it brings to the business.

Support the evolution of data science best practices, standards, documentation, and team learning.

Work on problems of diverse scope and apply sound judgment in selecting methods and techniques.

Build effective networks with senior internal and external stakeholders in your area of expertise.

Stay current on relevant external trends in data science, machine learning, and Agentic AI, and assess their applicability to General Mills business needs.

Demonstrate learning agility by applying new knowledge, tools, and methods to improve solution quality and delivery.

MINIMUM QUALIFICATIONS

Minimum qualification- Bachelor's in Technology/ Engineering/Science

Total analytics experience required6-8Years.

Expertise in supervised ML algorithms, regression, decision trees, ensemble models, time series, forecasting, neural networks.

Exposure to unsupervised learning and NLP.

Technical concepts and platforms- Proficiency on Google Cloud Platform, SQL, Python and R.

Experienced in constructing and solving Linear, Mixed integer, Constraint and nonlinear programming problems.

Should be comfortable in designing own heuristic algorithms or implementing any known heuristic approach.

Have worked in areas like network optimization, cutting stock, knapsack kind of problems.

Experience working with an Agile development methodology featuring sprints, point estimation and daily stand-ups.

Must have worked in at least a couple of major commercial/open source OR tools and software like python, Google OR tools, IBM IlogCplex,Gurobi, AIMMS, FICO express etc.

Domain Experience: Consumer Packaged Goods /Manufacturing/Retail/E-commerce/Energy/Sales/Commercial.

Excellentcollaboration andstorytelling skills.

PREFERRED QUALIFICATIONS

Knowledgeand usage of agentic / generative tools.

ELIGIBILITY

Applicants must meet minimum age qualifications in the country in which the job is located.

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