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The job description asks for Machine Learning, Deep Learning, Agentic AI, AI Agent Building, End-to-End Model Development, Predictive Modeling & Machine Learning, Advanced Analytics & Insights and Machie Learning Ops & Scalability. Make sure your resume shows the ones you have, in the words the job uses: applicant tracking systems look for them.

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This is based in Mumbai Metropolitan Region.

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Data Scientist II

General Mills

Mumbai Metropolitan Region

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.

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