ITQ Data Scientist II

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) 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 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 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 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 Required 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 Qualification 5+ years of experience Background in statistics or quantitative sciences Certifications in R, Python, or SQL ELIGIBILITY Applicants must meet minimum age qualifications in the country in which the job is located.