Data Scientist II

General Mills; Mumbai; On-site; INR 1,800,000 - 3,200,000; Full time

Job summary

General Mills through the Global Knowledge Solutions program seeks a Data Scientist II to design, build, and deploy autonomous AI systems using agentic architectures and GenAI techniques. This role focuses on end-to-end data science projects in R&D, product innovation, and quality, with emphasis on scalable AI solutions.

You will work with cross-functional teams, lead model development, and ensure production-ready pipelines while advancing AI safety and governance practices.

Qualifications

• Master’s or Ph.D. in Data Science, CS, Statistics, or related quantitative field.
• 5+ years building and deploying ML models, with agentic AI experience.
• Strong ML expertise: feature engineering, validation, ensemble models, neural networks.
• Proficiency in Python or R with pandas, NumPy, scikit-learn.
• Experience with PyTorch, TensorFlow, Keras.
• Hands-on MLOps, Git, and cloud platforms (AWS/GCP/Azure).
• Experience deploying production ML systems.
• Strong data storytelling and visualization skills (Shiny, Dash, Tableau).
• Ability to manage multiple projects independently.

Responsibilities

• Design AI agents using LLMs, RAG, memory and orchestration.
• Lead end-to-end data science projects from problem to deployment.
• Develop predictive models for business challenges in R&D, product, quality.
• Apply advanced analytics to extract insights from structured and unstructured data.
• Build and maintain data/model pipelines; production monitoring.
• Stay current with GenAI, autonomous agents, AI safety.
• Partner with clients to define objectives, timelines, and plans.
• Communicate analyses and insights through reports and meetings.
• Contribute to process improvements and upskill in ML/AI.
• Complete required trainings.

Skills

Python

R

pandas

NumPy

scikit-learn

PyTorch

TensorFlow

Keras

MLOps

Git

AWS

GCP

Azure

Tableau

Shiny

Dash

Education

Master’s or Ph.D. in Data Science, CS, Statistics or related field

Tools

Git

Jupyter

Job description

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.

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

The Global Knowledge Solutions (GKS) organization catalyzes the creation, transfer, and application of knowledge to ensure ITQ succeeds at its mission of driving internal and external innovation, developing differentiated technology, and engendering trust through food safety and quality.

The Data Scientist II in this program area is expected to: have deep expertise in Machine Learning, Deep Learning, and Agentic AI systems to drive high‑impact analytics and AI solutions. This role will focus on designing, building, and deploying intelligent, autonomous, and scalable AI systems that address complex business and R&D challenges; and manage multiple projects independently or with guidance. This role requires you to operate in 11.00 am to 8.00 pm shift.

Key Accountabilities

Technical Excellence (70%)

• AI Agent Building: Design AI agents leveraging LLMs, RAG, memory, tools, and orchestration frameworks. Implement multi‑step reasoning, task planning, and autonomous workflows using agentic architecture. Evaluate agent performance using custom evaluation metrics, simulators, and feedback loops. Stay current with emerging patterns in GenAI, autonomous agents, and AI safety.
• End-to-End Model Development: Independently lead data science projects through the entire lifecycle: from problem definition and data acquisition to feature engineering, model selection, and deployment.
• Predictive Modeling & Machine Learning: Design, build, and validate robust machine learning models (e.g., regression, classification, clustering, time-series forecasting) to solve key business challenges in R&D, product innovation, and quality.
• Advanced Analytics & Insights: Apply statistical inference, data mining, and advanced analytical techniques to extract actionable insights from complex structured and unstructured data (e.g., text, sensor data).
• Machie Learning Ops & Scalability: Build and maintain data and modeling pipelines. Deploy models into production environments and monitor their performance, ensuring scalability and reliability. Working experience on Computer-vision/Image analysis projects.
• Technical Innovation: Stay current with advances in data science and machine learning. Evaluate and implement new tools, frameworks (e.g., PyTorch, TensorFlow, Keras, scikit-learn), and methodologies to enhance the team's capabilities.

Business Partnership (15%)

• Work effectively with clients to identify client needs and success criteria, and translate into clear project objectives, timelines, and plans.
• Be responsive and timely in sharing project updates, responding to client queries, and delivering on project commitments.
• Clearly communicate analysis, conclusions, insights, and conclusions to clients using written reports and real‑time meetings.

Innovation & Continuous Improvement (10%)

• Improve processes and methodologies
• Develop new analytical capabilities
• Continuously upskill in ML and AI best practices

Administration (5%)

• Complete required trainings and organizational responsibilities

Minimum Qualifications

• Education: Master’s or Ph.D. in Data Science, Computer Science, Statistics, or related quantitative field
• Experience: 5+ years building and deploying ML models and working experience on Agentic AI
• Technical Skills: Strong ML expertise (feature engineering, validation, ensemble models, neural networks)
• Proficiency in Python/R (pandas, NumPy, scikit-learn, etc.)
• Experience with PyTorch, TensorFlow, Keras, or similar
• Hands‑on MLOps, Git, and cloud platforms (AWS/GCP/Azure)
• Experience deploying production ML systems
• Strong data storytelling and visualization skills (Shiny, Dash, Tableau)
• Ability to manage multiple projects independently

Preferred Qualifications

• Certifications in R, Python, or SQL

ELIGIBILITY

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