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Mid-level data scientist title with some brand visibility but niche optimization requirements reduce applicant density.
Role requires ML plus OR optimization and CPG/retail domain experience, making cross-industry fit limited.
Explicit 6-8 years plus mandatory ML, GCP, optimization solvers, and domain experience increases filter strictness.
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Design, develop, and deploy scalable AI and machine learning solutions across use cases such as demand forecasting, text classification, and logistics optimization.
Collaborate with ML and Systems Engineers to monitor and maintain production model performance, addressing degradation proactively.
Advocate for data science best practices and contribute to team learning, standards, and community of practice within General Mills.
Bachelor's degree in Technology, Engineering, or Science.
6-8 years of analytics experience with expertise in supervised ML algorithms including regression, decision trees, ensemble models, time series forecasting, and neural networks.
Proficiency in Google Cloud Platform, SQL, Python, R, and experience with commercial/open-source optimization tools like Google OR tools, IBM Ilog Cplex, or Gurobi.
Domain experience in Consumer Packaged Goods, Manufacturing, Retail, E-commerce, Energy, Sales or Commercial.
Experienced in solving complex optimization problems including linear, mixed integer, constraint and nonlinear programming, with ability to design heuristic algorithms.
Comfortable working in Agile development environments with sprint cycles and strong execution discipline.
Strong in stakeholder engagement and translating business needs into practical AI/ML solutions with measurable outcomes.