Data Science Manager - Hybrid

Key Skills

SAP, Python Programming, SQL, Azure, Machine learning techniques, Data science techniques, Writing, R Programming, Algorithms, SPARK Programming, Supply Chain Management, Logistic Regression, Effective communication skills, Business Analytics

Job Description

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.

Primary Responsibilities:

• 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.

Qualifications:

• 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.

Skills:

• Strong knowledge of analytical techniques in statistical modeling and machine learning. Experience in formulating and implementing statistical models.
• Familiarity with statistical/modeling programming.
• Experience with various statistical methodologies and mathematics (Generalized Additive Models (GAM), Hierarchical Linear Mixed Effects (HLM) Regression, Generalized Linear Models (GLM), Classification and Regression ensembling, Latent Analysis and Structural Equation Modeling (SEM), and unsupervised clustering segmentation models).
• Proficiency with ERP systems (e.g., SAP) and Microsoft Office.
• Ability to strategically influence leadership, stakeholders and partners.
• Excellent interpersonal and customer service skills, including aptitude for mentoring and coaching others.
• Strong business acumen (understanding of how business operates, and how to harness data and analytics to meet business needs).
• Ability to develop and deploy advanced analytical models and algorithms that drive profitable growth at NUSA.
• Experience modeling and productionalizing models in notebook environments (Microsoft Azure preferred).
• Passion for solving complex data problems and generating cross-functional solutions in a fast-paced environment.
• Proven examples of developing, selling, and sharing modeling concepts across team members to drive adoption and implementation beyond personal use.
• Excellent oral and written communication skills, organizational and time-management abilities.
• High initiative, self-starter, and able to work with limited supervision.
• Candidates with experience working in large, complex, multinational organization are preferred.
• Experience with machine learning methodologies and algorithms (Regression, Bayesian statistics, Clustering, Classification, Probability Networks, etc.) in a Consumer Packaged Goods industry or context preferred.

Li-Hybrid

Requisition ID: 282729

It is our business imperative to remain a very inclusive workplace.

To our veterans and separated service members, you're at the forefront of our minds as we recruit top talent to join Nestlé. The skills you've gained while serving our country, such as flexibility, agility, and leadership, are much like the skills that will make you successful in this role. In addition, with our commitment to an inclusive work environment, we recognize the exceptional engagement and innovation displayed by individuals with disabilities. Nestlé seeks such skilled and qualified individuals to share our mission where you’ll join a cohort of others who have chosen to call Nestlé home.

The Nestlé Companies are an equal employment opportunity and affirmative action employer seeking diversity in qualified applicants for employment. All applicants will receive consideration for employment without regard to race, ethnicity, color, gender, gender identity, age, religion, national origin, ancestry, disability, perceived disability, medical condition, genetic information, veteran status, sexual orientation, or any other protected status, as defined by applicable law. Prior to the next step in the recruiting process, we welcome you to inform us confidentially if you may require any special accommodations in order to participate fully in our recruitment experience. Contact us at accommodations@nestle.com or please dial 711 and provide this number to the operator: 1-800-321-6467.

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