Lead Data Scientist (Hybrid)

 

Foods people love. Brands people trust. And a career that nourishes your future like no other.

 

If you're driven by the passion to do something meaningful that changes lives, Nestlé is the place for you. Nestlé USA is one of seven operating companies that make up Nestlé’s presence in the United States. We're in 97% of American homes, and as the leading food and beverage company, our goals are to continue to deliver quality food and beverage products, strengthen our local communities, and reduce our environmental and climate impact.

 

We’re determined to challenge the status quo and be better tomorrow than we are today. As individuals and teams, we embrace our entrepreneurial culture and have created a workplace where collaboration is essential, courage is rewarded, speed is expected, and agility is the norm to delight our consumers every single day. Here, you will find limitless opportunities to learn and advance your career and feel empowered to succeed in the workplace and beyond. Because our focus is not only on nourishing our customers, but also about enriching you.

 

This position is not eligible for Visa Sponsorship.

 

 

Position Summary

As a “Business Scientist” (Business Acumen + Data Scientist), the Enterprise Analytics (EA) Lead Data Scientist will serve as the advanced analytics expert across EA initiatives currently in flight or being planned at NUSA, building, enhancing and applying sophisticated, interconnected and predictive algorithms to drive profitable growth across the enterprise. The overall objective is to enable diagnostic evaluation, predictive planning, and prescriptive decision making in everyday problem solving across the Ensure Supply Functions (Procurement, Manufacturing, and Logistics), with a primary focus in Manufacturing.

• Lead model development, evaluation, and deployment to support operational decision making across Ensure Supply, focusing mostly in Manufacturing.
• Introduce Machine Learning methodologies across a wide breadth of business use cases.
• Acquire deep understanding of business problems and translate them into appropriate mathematical depictions.
• Act as an internal consultant by integrating with departmental customers to identify opportunities, scope and define the business problems, performing data analysis, and generate self-service solutions to address needs.
• Interpret the results, draw conclusions, and present findings / recommendations to appropriate groups to help identify actionable steps to be taken by cross-functional and leadership teams.
• Mentor more junior staff, guide predictive model development across team, define how customers use the models, and train users on integration.

 

Primary Responsibilities – What You’ll Do

• Test and implement the advanced analytics methods to derive insights that drive business growth.
• Drive the execution of AI solutions to address business needs.
• Drive EA priorities through rapid piloting and scaling of next gen technologies.
• Incorporate the latest data science thinking into NUSA’s solutions and models.
• Collect, cleanse, and understand complex data sources to enable proper analytical modeling.
• Research, design, develop, test, and implement data science methodologies across a wide range of business applications.
• Define and develop programming for self-service decision support solutions that leverage predictive, prescriptive, and scenario optimization tactics.
• Manage Special Projects, Pilots, Proof of Concepts, and Ad-hoc project work leading the charge from idea to delivered data science capability.
• Participate in the evaluation, intake, design, and integration strategy between multiple commercial functions (sales, marketing, etc.) and data sources for varying Nestlé businesses.
• Conduct proper stakeholder management to ensure all parties are aligned and updated throughout project life cycle.
• Design and build advanced visualization tools that will simplify the outputs of the models, with the goal of being integrated into a self-service operational model across the business stakeholders.
• Develop professional presentations and project status reporting appropriate for their intended audience.