ITQ Data Scientist II
General Mills
ITQ Data Scientist II
Job Description
COMPANY OVERVIEWWe 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.
OverviewThe Global Knowledge Solutions (GKS) team enables innovation, product development, and quality excellence across ITQ.The Data Scientist II will design, build, and deploy scalable machine learning and AI solutions to solve complex R&D, consumer research, and quality challenges. This role requires deep expertise in ML, Deep Learning, MLOps, and Agentic AI systems, with the ability to independently lead end-to-end projects.Key ResponsibilitiesTechnical Excellence (70%)Lead full ML lifecycle: problem framing → data prep → modeling → deploymentBuild predictive models (regression, classification, clustering, time-series)Apply statistical and advanced analytics to structured & unstructured dataDevelop scalable ML pipelines and deploy models to productionDesign and implement AI agents using LLMs, RAG, memory, tools, and orchestration frameworksEvaluate and optimize AI systems using custom metrics and feedback loopsStay current with emerging ML and GenAI advancementsBusiness Partnership (15%)Translate business needs into analytical solutionsCommunicate insights clearly to technical and non-technical stakeholdersDeliver projects on time with defined success criteriaInnovation & Continuous Improvement (10%)Improve processes and methodologiesDevelop new analytical capabilitiesContinuously upskill in ML and AI best practicesAdministration (5%)Complete required trainings and organizational responsibilitiesMinimum QualificationsEducation: Master’s or Ph.D. in Data Science, Computer Science, Statistics, or related quantitative fieldExperience: 5+ years building and deploying ML modelsRequired SkillsStrong ML expertise (feature engineering, validation, ensemble models, neural networks)Proficiency in Python/R (pandas, NumPy, scikit-learn, etc.)Experience with PyTorch, TensorFlow, Keras, or similarHands-on MLOps, Git, and cloud platforms (AWS/GCP/Azure)Experience deploying production ML systemsStrong data storytelling and visualization skills (Shiny, Dash, Tableau)Ability to manage multiple projects independentlyPreferred Qualification5+ years of experienceBackground in statistics or quantitative sciencesCertifications in R, Python, or SQL
ELIGIBILITYApplicants must meet minimum age qualifications in the country in which the job is located.
Locations
- MH, Mumbai, Powai
Skills Required
- Python/Rintermediate
- PyTorchintermediate
- statisticsintermediate
Required Qualifications
- Education: Master’s or Ph.D. in Data Science, Computer Science, Statistics, or related quantitative fieldExperience: 5+ years building and deploying ML models (experience, 5 years)
- Strong ML expertise (feature engineering, validation, ensemble models, neural networks) (experience)
- Proficiency in Python/R (pandas, NumPy, scikit-learn, etc.) (experience)
- Experience with PyTorch, TensorFlow, Keras, or similar (experience)
- Hands-on MLOps, Git, and cloud platforms (AWS/GCP/Azure) (experience)
- Experience deploying production ML systems (experience)
- Strong data storytelling and visualization skills (Shiny, Dash, Tableau) (experience)
- Ability to manage multiple projects independently (experience)
- Strong ML expertise (feature engineering, validation, ensemble models, neural networks) (experience)
- Proficiency in Python/R (pandas, NumPy, scikit-learn, etc.) (experience)
- Experience with PyTorch, TensorFlow, Keras, or similar (experience)
- Hands-on MLOps, Git, and cloud platforms (AWS/GCP/Azure) (experience)
- Experience deploying production ML systems (experience)
- Strong data storytelling and visualization skills (Shiny, Dash, Tableau) (experience)
- Ability to manage multiple projects independently (experience)
Preferred Qualifications
- 5+ years of experience (experience, 5 years)
- Background in statistics or quantitative sciences (experience)
- Certifications in R, Python, or SQL (certification)
- 5+ years of experience (experience, 5 years)
- Background in statistics or quantitative sciences (experience)
- Certifications in R, Python, or SQL (certification)
Responsibilities
- Technical Excellence (70%)
- Lead full ML lifecycle: problem framing → data prep → modeling → deployment
- Build predictive models (regression, classification, clustering, time-series)
- Apply statistical and advanced analytics to structured & unstructured data
- Develop scalable ML pipelines and deploy models to production
- Design and implement AI agents using LLMs, RAG, memory, tools, and orchestration frameworks
- Evaluate and optimize AI systems using custom metrics and feedback loops
- Stay current with emerging ML and GenAI advancements
- Lead full ML lifecycle: problem framing → data prep → modeling → deployment
- Build predictive models (regression, classification, clustering, time-series)
- Apply statistical and advanced analytics to structured & unstructured data
- Develop scalable ML pipelines and deploy models to production
- Design and implement AI agents using LLMs, RAG, memory, tools, and orchestration frameworks
- Evaluate and optimize AI systems using custom metrics and feedback loops
- Stay current with emerging ML and GenAI advancements
- Business Partnership (15%)
- Translate business needs into analytical solutions
- Communicate insights clearly to technical and non-technical stakeholders
- Deliver projects on time with defined success criteria
- Translate business needs into analytical solutions
- Communicate insights clearly to technical and non-technical stakeholders
- Deliver projects on time with defined success criteria
- Innovation & Continuous Improvement (10%)
- Improve processes and methodologies
- Develop new analytical capabilities
- Continuously upskill in ML and AI best practices
- Improve processes and methodologies
- Develop new analytical capabilities
- Continuously upskill in ML and AI best practices
- Administration (5%)
- Complete required trainings and organizational responsibilities
- Complete required trainings and organizational responsibilities
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