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Job Location: Minneapolis, MN
Job Description:
OVERVIEW
RESPONSIBILITIES
MINIMUM QUALIFICATIONS
ADDITIONAL CONSIDERATIONS
OVERVIEW
To make the food people love, we need to make sure we 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 advanced expertise in machine learning, optimization and information retrieval to design, prototype and build a next generation supply chain engine and services. You will serve as the technical leader for an enterprise level supply chain data science initiative. You will be responsible for designing the analytic architecture, constructing machine learning models, and communicating with product owners, business partners and other data scientists.
RESPONSIBILITIES
- Work closely with data science leadership, engineering, and business partners to develop optimization and machine learning models using best in class tools and technology.
- Create production ready, scalable models that provide real time insights that align with General Mills technology standards.
- Serve as a senior leader as part of the data science leadership team- contribute to technical strategy, best practices, and team development.
- Mentor and coach junior data scientist on key technical and domain topics.
- Act as a thought leader in supply chain data science techniques and represent the Digital and Technology organization.
- Partner with functional analytic teams to align and integrate solutions.
MINIMUM QUALIFICATIONS
- Master’s degree in computer science, operations research, engineering or related quantitative field or commensurate work experience in supply chain technology or data science.
- 5+ years of professional experience developing and deploying machine learning algorithms in a production environment.
- Proficient in one or more coding languages including Python
- Experience with graph database technology preferred
- Expertise with leading the development of large-scale optimization, simulation, and network-based models.
- Highly adaptable, curious, and willing to work independently on complex and challenging problems.
ADDITIONAL CONSIDERATIONS
- The preferred location for this role is Minneapolis, MN however remote work-at-home applications within the United States, Canada or the UK will be considered.
- Relocation or international remote working arrangements (outside of the US) will not be considered.
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