Lead Statistical Forecaster and Data Scientist

Key Skills

Apache Hadoop, C Programming, C++, Data science techniques, Java Programming, Machine learning techniques, MapReduce, Python Programming, PyTorch, R Programming, Scala Programming, SQL, TensorFlow

Job Description

The Lead Supply Chain Planning Statistical Forecaster and Data Scientist will act as an individual contributor in managing the legacy Statistical forecasting solution and the deployment of PepsiCo's New Forecast to Schedule (FTS) statistical forecasting environment. The chosen candidate is expected to have a strong background in one or all the following functions: demand planning, statistical forecasting, supply planning and material resource planning. As well as a strong background in building and maintaining Advanced predictive models. This role will partner extensively across the organization with the PBNA PGT project team, sector/division planning leaders, IT and external partners on the project (IBM and SAP).

Responsibilities:

• Oversee and maintain the Statistical Forecasting Solution for Demand planning for both WHD (SAS) and DSD (SAP IBP) Businesses
• Champion the design & execution of advanced predictive modeling, ML, and AI solutions used to address specific business problems determined through consultation with business partners.
• Continuous improvement of systems, tools, and processes in support of FTS (Forecast to schedule) and SAS HPF
• Lead post performance forecast analytics to determine root cause of performance gaps and generate modeling solutions
• Maintaining Tableau and Power BI Reporting for supply chain planning
• Influencing organization and leadership on analytical strategy.
• Provide SME knowledge and experience to project (PGT) cut-over activities within demand planning, supply planning and Inventory optimization.
• Be a results-oriented “change agent” who can understand and help script/facilitate testing of business scenarios for FTS

Compensation and Benefits:

• The expected salary range is $91,000 - $140,000.
• Bonus based on performance and eligibility; target payout is 10% paid out annually.
• Paid time off subject to eligibility, including paid parental leave, vacation, sick, and bereavement
• Other benefits, subject to elections and eligibility:? Medical, Dental, Vision, Disability, Health and Dependent Care Reimbursement Accounts, Employee Assistance Program (EAP), Insurance (Accident, Group Legal, Life), Defined Contribution Retirement Plan

Qualifications/Requirements

• Bachelor’s in Mathematics, Statistics, computer Science, Database Management or other technical degree (Masters Preferred).
• 3-5 Years’ experience in a corporate environment; experience in CPG or retail planning environment preferred.
• Experience with Statistical Forecasting and building Predictive, Machine Learning, and/or AI models
• Advanced programming ability in SAS / SQL / Python / R
• Familiar with SAS HPF (High Performance Forecasting)
• Familiar with SAP and IBP
• Experience working with Teradata, SQL Server, Cloud based services
• Experience with Tableau, Power BI, SAP SAC and similar tools
• Ability to support continuous improvement or capability development work streams including scope definition, analysis, recommendations, and implementation.
• Ability to present quantitative data in an easy-to-understand manner that balances both analytics as well as business implications.
• Effective communication skills, with ability to work across and present to multiple levels and different organizational functions.
• Cross functional experience working with other functions, e.g., Sales, Finance and other Supply Chain functions.
• Must be willing and able to travel 5-10% of the time.