General Mills
Lead D&T Data Scientist - Optimization (Minneapolis Preferred, Remote Eligible)
General Mills, Minneapolis, Minnesota, United States, 55400
Job Overview
Do you see patterns or opportunities that others don’t see? Do you enjoy asking questions and analyzing data to deepen your knowledge? Do you like to challenge historical assumptions and recommend new ways to drive action based on data-driven insights? To make the food people love, we need to feed our decision makers the right data and solutions at the right time, every time. As a Lead Data Scientist at General Mills, you will apply your strong expertise in Statistics, Mathematics, Data Science, AI, Machine Learning, data mining, and information retrieval to design, prototype, and build next-generation advanced analytics engine and services. You will collaborate with product owners, business partners, and other Data Scientists in the consumer marketing and media space to define a technical problem statement and hypothesis to test. In addition, you will develop efficient and accurate analytical models that mimic business decisions. Key Accountabilities
Work closely with data science leadership, machine learning engineering, and business partners/product owners to develop optimization and machine learning models using best-in-class tools and technology. Provide data science leadership through strong partnership, actionable insights, strategic and tactical technical roadmap recommendations. Construct production-ready, reusable, large-scale or scalable complex optimization, simulation & machine learning models that provide real-time insights aligning with General Mills technology standards. Design and development of a modelling framework and architecture for deterministic/combinatorial optimization and advanced machine learning to solve complex problems in areas such as supply–demand planning, logistics, trade optimization, pricing, etc. Be a storyteller to explain the ‘why and how’ of data-driven recommendations to cross-functional teams. Counsel and advise business partners on technical solutions. Serve as a senior leader as part of the data science leadership team—contribute to technical strategy, best practices, and team development. Coach junior data scientists on key technical and domain topics through solution reviews and mentoring. Responsible for monitoring and improving model performance metrics in terms of accuracy and quality of recommendations, with feedback incorporated from business partners. Collaborate with colleagues, ask questions, engage, and solicit feedback from other Data Scientists. Participate in activities such as strategic planning and modeling documentation in addition to project-based work. Minimum Qualifications
6+ years of relevant data science experience with at least 4 years of experience in optimization. Bachelor’s Degree required in quantitative fields such as operations research, statistics, industrial engineering, or related disciplines. High proficiency with Python for developing optimization models using different types of commercial solver suites. Hands-on experience building IP / MIP models with supporting algorithms. Comfortable working with large and dynamic data frames and writing complex SQL queries. Highly adaptable, curious, and able to work independently on complex problems. Proven track record of partnering with business leaders and influencing key decisions. Bias for action with the ability to deliver outstanding results through prioritization and time management. Preferred Qualifications
Master’s degree in quantitative fields (Operations Research, Statistics, Industrial Engineering) or computer science with relevant work experience in supply chain, trade, pricing technologies, or data science. Relevant data science experience with a preference for optimization/operations research. Experience with Google Cloud Platform or other cloud platforms. Experience building optimization and simulation models using a commercial solver like Gurobi on a cloud stack is a plus. Additional Considerations
The preferred location for this role is Minneapolis, MN; however, remote work-from-home applications within the United States will be considered. Relocation or international remote working arrangements (outside of the US) will not be considered. Salary Range
The salary range for this position is $126,700.00 - $211,200.00 annually. Total rewards include health benefits, retirement and financial wellbeing programs, time off, wellbeing support, and perks. Pay may vary based on education, experience, certifications, and other factors. An incentive program may be available depending on performance. Reasonable Accommodation Request
If you need to request an accommodation during the application or hiring process, please fill out our online accommodations request form. Seniority level
Mid-Senior level Employment type
Full-time Job function
Engineering and Information Technology Industries
Manufacturing, Food and Beverage Services, and Food and Beverage Manufacturing
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Do you see patterns or opportunities that others don’t see? Do you enjoy asking questions and analyzing data to deepen your knowledge? Do you like to challenge historical assumptions and recommend new ways to drive action based on data-driven insights? To make the food people love, we need to feed our decision makers the right data and solutions at the right time, every time. As a Lead Data Scientist at General Mills, you will apply your strong expertise in Statistics, Mathematics, Data Science, AI, Machine Learning, data mining, and information retrieval to design, prototype, and build next-generation advanced analytics engine and services. You will collaborate with product owners, business partners, and other Data Scientists in the consumer marketing and media space to define a technical problem statement and hypothesis to test. In addition, you will develop efficient and accurate analytical models that mimic business decisions. Key Accountabilities
Work closely with data science leadership, machine learning engineering, and business partners/product owners to develop optimization and machine learning models using best-in-class tools and technology. Provide data science leadership through strong partnership, actionable insights, strategic and tactical technical roadmap recommendations. Construct production-ready, reusable, large-scale or scalable complex optimization, simulation & machine learning models that provide real-time insights aligning with General Mills technology standards. Design and development of a modelling framework and architecture for deterministic/combinatorial optimization and advanced machine learning to solve complex problems in areas such as supply–demand planning, logistics, trade optimization, pricing, etc. Be a storyteller to explain the ‘why and how’ of data-driven recommendations to cross-functional teams. Counsel and advise business partners on technical solutions. Serve as a senior leader as part of the data science leadership team—contribute to technical strategy, best practices, and team development. Coach junior data scientists on key technical and domain topics through solution reviews and mentoring. Responsible for monitoring and improving model performance metrics in terms of accuracy and quality of recommendations, with feedback incorporated from business partners. Collaborate with colleagues, ask questions, engage, and solicit feedback from other Data Scientists. Participate in activities such as strategic planning and modeling documentation in addition to project-based work. Minimum Qualifications
6+ years of relevant data science experience with at least 4 years of experience in optimization. Bachelor’s Degree required in quantitative fields such as operations research, statistics, industrial engineering, or related disciplines. High proficiency with Python for developing optimization models using different types of commercial solver suites. Hands-on experience building IP / MIP models with supporting algorithms. Comfortable working with large and dynamic data frames and writing complex SQL queries. Highly adaptable, curious, and able to work independently on complex problems. Proven track record of partnering with business leaders and influencing key decisions. Bias for action with the ability to deliver outstanding results through prioritization and time management. Preferred Qualifications
Master’s degree in quantitative fields (Operations Research, Statistics, Industrial Engineering) or computer science with relevant work experience in supply chain, trade, pricing technologies, or data science. Relevant data science experience with a preference for optimization/operations research. Experience with Google Cloud Platform or other cloud platforms. Experience building optimization and simulation models using a commercial solver like Gurobi on a cloud stack is a plus. Additional Considerations
The preferred location for this role is Minneapolis, MN; however, remote work-from-home applications within the United States will be considered. Relocation or international remote working arrangements (outside of the US) will not be considered. Salary Range
The salary range for this position is $126,700.00 - $211,200.00 annually. Total rewards include health benefits, retirement and financial wellbeing programs, time off, wellbeing support, and perks. Pay may vary based on education, experience, certifications, and other factors. An incentive program may be available depending on performance. Reasonable Accommodation Request
If you need to request an accommodation during the application or hiring process, please fill out our online accommodations request form. Seniority level
Mid-Senior level Employment type
Full-time Job function
Engineering and Information Technology Industries
Manufacturing, Food and Beverage Services, and Food and Beverage Manufacturing
#J-18808-Ljbffr