Job Overview |
Role: Sr. D&T Data Scientist Location: Mumbai, Hybrid General Mills, Digital and Technology India, is seeking a Sr Data Scientist to join the Data Science team. Data Scientists within our team are dedicated to build enterprise intelligent automations and enable Core ML, Deep Learning, Generative AI solutions on various use cases in CPG. They are also responsible for curating a community of practice to determine the best standards and practices around data science at General Mills. |
Role Responsibilities |
Deliver on business problems: - Lead, design, and execute novel ways to help business partners achieve objectives through analysis and modelling.
- Lead the design & implementation of Generative AI, Agentic AI, LLM & NLP solutions for unstructured text and images, structured data, covering problem framing, data curation, finetuning, and evaluation across classification, entity extraction & summarization.
- Partner closely with AI Leadership, ML Engineering, and business stakeholders to architect highquality Agentic AI and RAG workflows, optimizing ingestion, chunking, embeddings and vector indexing with established frameworks and stores to maximize retrieval performance.
- Design and maintain business semantics (ontologies, taxonomies, and metadata standards) so that Agentic AI and RAG systems retrieve and reason over information using consistent business concepts (brands, categories, customers, channels, plants, regions, etc.)
- Create production ready, scalable models that provide real-time insights that align with General Mills technology standards.
- Recognizes opportunities to apply external industry trends and implements them within role.
Consultation: - Provide technical leadership through strong partnership and by offering alternative solutions.
- Provide technical leadership for analytical solution design by hypothesisdriven experimentation, defining robust evaluation strategies and error taxonomies with humanintheloop reviews, with clear documentation for transparency and reusability.
- Lead Interactions with stakeholders to learn on problem statement and drive results.
- Be an advocate for data science team.
- Constructively challenge the other data scientists on approach
- Contribute to best practices as we evaluate new platforms, tools and pipelines.
- Coach Jr. Data Scientist / Interns / Contractors on key technical and domain topics through solution reviews and mentoring.
- Collaborate with analytic leaders across functions.
- Provide consultation and review the deliveries for other data scientists.
Stakeholder Management: - Manage the assigned priorities, consistency of execution and managing resources.
- Act as a thought leader in data science techniques and represent the Digital and Technology organization.
- Contributing towards Data Science technical strategy, best practices, and team development.
- Champion Responsible AI by ensuring privacy, security, and governance compliance reducing model errors and bias and partnering across teams to integrate solutions into daily work.
- Develop trust and credibility with business leade rs.
- Educate stakeholders on the GCP analytic practices.
- Closely collaborates with the stakeholders on projects and data science leaders to ensure practices are developed and enhanced to support accelerated analytic development and maintainability.
Collaboration: - Collaborates with ML engineers and systems engineers to ensure the models are deployed in a scaled and optimized way. Additionally ensure support the post-production to ensure model performance degrades are proactively managed.
- Work closely with data science leadership, engineering, and business partners to develop machine learning models using best-in-class tools and technology.
Networks with senior internal and external personnel in own area of expertise.
Lead research work to new analytic trends aligned to business.
Leverage and contribute to new open-source innovation.
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Must - have technical skills and experience |
(Expert in section2 with exposure to section1) Section1-Generative AI/Agentic AI - Proven experience in leading the design and implementation of complex data science solutions, particularly in LLM, NLP, Agentic AI, and RAG
- Proficiency in designing and implementing LLM and NLP solutions, including problem framing, data curation, fine-tuning, and evaluation (classification, entity extraction, summarization).
- Strong understanding and experience in architecting high-quality Agentic AI and RAG workflows, including data ingestion, chunking, embeddings, vector indexing, and optimizing retrieval performance using established frameworks and vector stores.
- Ability to co-create production-ready, scalable models that provide real-time insights, adhering to technology standards (implies MLOps practices).
- Expertise in hypothesis-driven experimentation, defining robust evaluation strategies, error taxonomies, and human-in-the-loop reviews.
- Knowledge and application of Responsible AI principles, including privacy, security, governance compliance, bias reduction, and model interpretability.
- Proficiency with best-in-class tools and technologies (e.g., Python, LangChain, Lang Graph, Google ADK, Google Cloud Platform)
- Track record of creating models that are deployed in a production environment
Section-2- AI/ML - Expertise in supervised ML algorithms, regression, decision trees, ensemble models, time series, forecasting, neural networks
- Proven implementation of ML and AI practices
- Exposure to unsupervised learning and NLP
- Technical concepts and platforms- MLOps, Containerization, Data Lineage and Visualization
- Proficiency on Google Cloud Platform, SQL and Python
Other expertise and experience - Minimum qualification- bachelor's degree (full time)
- Total analytics experience required 10-12 Years
- Bachelor's or Master degree in computer science/ Artificial Intelligence/ Machine Learning /Statistics/Applied Mathematics from Tier 1 institute
- Proficiency in FMCG/CPG domain
- Experience working with an Agile development methodology featuring sprints, point estimation and daily stand-ups
- Excellent stakeholder management skills and storytelling skills
- Demonstrates learning agility and ability to apply to work.
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Good to have skills:- |
Knowledge of Machine Learning/Deep Learning/Operations Research |
Skill proficiency expectations |
Expert Level | Intermediate Level | Basic Level | . NLP, Generative AI, Agentic AI . RAG Architecture . Google Cloud Platform - Vertex AI, BQ, Composer . FMCG/CPG domain . Python, LangChain, ADK . ML supervised algorithms | . Google Cloud Architecture . MLOps | . Deep Learning |
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