Data Science Manager - Hybrid

The Data Science Manager will lead the Statistical Modeling team and will be responsible for all projects that requires statistical modeling serving Supply Chain, e-Commerce, and Sales. Work with various functional teams such as Demand and Supply Planning, Physical Logistics, Finance, IT to make sure that the key priorities for Nestle US, most heavily Supply Chain, where statistical modeling is required can be executed smoothly.

This position will also be responsible for:

• Creating a strategy for Forecasting as a Service within Nestle USA, which includes expanding the scope and impact of the service.
• Influencing organization and leadership on forecasting strategy.
• Staying up to date with statistical forecasting technology and business trends.
• Identifying and developing forecast improvement opportunities within the organization that lead to major financial impact.
• Playing a critical role of forecasting solution visionary and overall management of forecasting solution development cycle.
• Coaching and reviewing work of team members on their projects
• Scoping major projects to define an appropriate approach to be applied.
• Leading, managing and QAing forecasting projects to minimize risk and ensure success.

• Build and lead a group of analytical experts who will provide statistical modeling and predictive analytics solutions to improve supply chain performance. Lead and manage a team of statistical analysts supporting various areas within Nestle USA as a service.
• Build deep relationships with Supply Chain and related business areas to understand and develop statistical analytics solutions for key business needs. Generate demand by translating business needs to statistical analytics projects across functional areas. Understand the business issues and opportunities for each product area and how statistical analytics can add value. Work together with various functional teams to align on business requirements and resolve issues.
  
  Work closely with the development team to ensure quality of solution.
• Own and manage NUSA statistical forecasting generation activities. Support demand planning forecast process, identification of gaps between actuals and forecasted values. Collaborate with supported functions to meet and exceed their service expectations.
• Work with the Functional and IT Leadership Teams to coordinate and prioritize issues, projects, and initiatives.
• Manage, coach, and develop the Statistical Modeling team so that they will be ready to take on positions of increased responsibility within the company.
• Lead the recruiting efforts for the department, identifying internal and external candidates to ensure a highly skilled pipeline of talent.
• Manage projects, pilots, Proof of Concepts/Value (POC/POV), and ad-hoc projects, ensuring on-time delivery according to a master project plan. This includes appropriate communication to various audiences and development/alignment of the project plan and success criteria.
• Conduct proper stakeholder management to ensure all parties are aligned and updated throughout the project life cycle.
• Act as a consultant in the capacity of publishing, educating, and securing acceptance of complex mathematical concepts and models from various stakeholders.
• Develop professional presentations and project status reporting appropriate for their intended audience.

• Undergraduate Degree in Computer Science, Engineering, Mathematics, Statistics, Business, or a similar field;
  Master’s degree preferred.
• Minimum of 8 years relevant experience, which may include Statistical Modeling, Predictive Analytics, Operations Research, Information Systems and/or Business Analysis. Note a Master’s Degree and other advanced degree can be considered in lieu of experience.
• At least 1 to 2 years of people leadership experience.
• 3+ years of experience using various programming languages (R, Python, Spark, SQL)
• Experience in supply chain and logistics utilizing advanced analytics to perform Statistical Forecasting and Predictive Analytics.
• Consumer products industry experiences a plus.

• Strong knowledge of analytical techniques in statistical modeling and machine learning. Experience…