Overview
With data deeply embedded in our DNA, PepsiCo Data, Analytics and AI (DA&AI) transforms data into consumer delight. We build and organize business-ready data that allows PepsiCo's leaders to solve their problems with the highest degree of confidence. Our platform of data products and services ensures data is activated at scale. This enables new revenue streams, deeper partner relationships, new consumer experiences, and innovation across the enterprise
The Data Science (DS) Pillar in DA&AI will be the organization where Data Scientist and ML Engineers report to in the broader D+A Organization. Also DS will lead, facilitate and collaborate on the larger DS community in PepsiCo. DS will provide the talent for the development and support of DS component and its life cycle within DA&AIProducts. And will support "pre-engagement" activities as requested and validated by the prioritization framework of DA&AI
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Position Overview:
Your role will be to be part of growing team based in Dallas, to create and support global digital developments for PepsiCo. These developments will be around topics like revenue management, supply chain, manufacturing, logistics. You will be part of a collaborative interdisciplinary team around data, where you will be responsible of building deployable statistical/machine learning/AI models, starting from the discovery phase
The main objective of the Data Science FLNA Director is to lead the Integrated Business Planning (IBP) deployment for PepsiCo Foods North America (PFNA). This is both and execution and strategic role that requires extensive experience in deploying technical solutions plus expertise in business applications of data science and areas of Demand Planning, S&OE and S&OP. This role will also take charge of building and deploying solutions that connect IBP to the Trade Promotion Management (TPM) solution in use in North America (both food and beverage units), and maintaining and expanding the use of other legacy trade promotion analytic solutions (Post Event Analytics) across North America
You will coordinate closely with IBP Program leadership, the IBP data science Lead and its Leadership (IBP Build, IBP US Delivery), working as part of that team. This role will orchestrate both the delivery and customization of the analytics components built to-date, which will be done with internal and external talent
You will work closely with process owners, product owners and final business users. This will provide you the correct visibility and understanding of criticality of your developments. Focus of the role will be demand forecasting and other associated analytics
You will be an internal ambassador of the team's culture around data and analytics and become a champion of talent development. You will provide stewardship to colleagues in the areas that you are and specialist or you are specializing
Responsibilities
- Accountable for delivering the data science activities in IBP program in large and complex North America markets (PFNA focus)
- Collaborate with and influence executives across the global markets (IBP, Strategy, Sector and Transformation leads, etc.) to drive alignment and manage the narrative around data science and analytics applied to IBP
- Lead a team that deploys and sustains data science components for IBP with focus in FLNA market; focus team on applying the right tools in artificial intelligence, machine learning, and analytics in precise, scalable, secure and ethical ways
- Lead key aspects of the deployment of IBP programs. Both Data Science activities leaning on the configuration of reusable IBP data science assets and creation of new assets to support the IBP FLNA deployments. Lead a group of ML Engineers to ensure that data/features are correctly coded for the use of our Data Science assets, pipelines get correctly deployed, scalable and execute in allocated service level agreements
- Manage key business and transformation stakeholder expectations, alignment and conversations through program operational and strategic working sessions
- Mediate and negotiate conversations and work with other data organizations (Data/AI Program Manager, Enterprise Data Operations, Data Governance, IBP Forecasting pod, sector teams and other IBP pods)
- Understand external environment and industry and incorporate the latest advances in data science technology and best practices in IBP use cases and other related enabling programs
- Lead and execute parallel IBP programs. One key program is the "Magic Triangle" that will aim to connect IBP demand planning forecasting with Trade Promotion Management (Commercial) forecasting and with financial forecasting
- Lead other FLNA sector-based programs assigned to the IBP team
- Oversee and report on data science work on IBP global deployments
- Lead other team members in the different digital projects acting as a data science lead for the project
- Act as a subject matter expert across different digital projects
- Act as stream leader in innovation activities
- Partner with product managers in taking DS requirements and assessing DS components in roadmaps
- Partner with data engineers to ensure data access for discovery and proper data is prepared for model consumption
- Partner with ML engineers working on industrialization
- Coordinate work activities with Business teams, other IT services and as required
- Drive the use of the Platform toolset and to also focus on 'the art of the possible' demonstrations to the business as needed
- Communicate with business stakeholders in the process of service design, training and knowledge transfer
- Support large-scale experimentation and build data-driven models
- Set KPIs and metrics to evaluate analytics solution given a particular use case
- Refine requirements into modelling problems
- Influence product teams through data-based recommendations
- Research and enable adoption of state-of-the-art methodologies
- Create documentation for learnings and knowledge transfer
- Have a mindset of reuse: Lead the identification and creation of reusable packages or libraries
Compensation & Benefits:
- The expected compensation range for this position is between $122,300 - $242,700
- Location, confirmed job-related skills and experience will be considered in setting actual starting salary
- Bonus based on performance and eligibility; target payout is 25% of annual salary paid out annually and an additional target payout of 10% of annual salary is paid out over 3 years following the end of the performance period
- Long term incentive equity may be awarded based on eligibility and performance
- Paid time off subject to eligibility, including paid parental leave, vacation, sick, and bereavement
- In addition to salary, PepsiCo offers a comprehensive benefits package to support our employees and their families, 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
- 13+ years industry experience and in leadership roles
- 8+ years leading team delivering production level analytical solutions with forecasting solutions as a plus
- 8+ years' experience in ETL and/or data wrangling techniques with deep understanding of data management approaches
- 8+ years' experience in Statistical/ML/AI techniques to solve supervised (regression, classification) and unsupervised problems, with focus on time series forecasting. Experiences with Deep Learning are a plus
- 8+ years' experience in developing business problem related statistical/ML modeling with industry tools with primary focus on Python or Scala development or other relevant toolsets
- Business storytelling and communicating data insights in business consumable format. Fluent in one Visualization tool
- Strong communications and organizational skills with the ability to deal with ambiguity while juggling multiple priorities and workstreams
- Experience with Agile methodology for team work and analytics 'product' creation. Fluent in Jira, Confluence
- Experience with Azure cloud services is a must
- Experience with time series forecasting
- Experience in Reinforcement Learning is a plus
- Experience in Simulation and Optimization problems in any space is a plus
- Experience with Bayesian methods is a plus
- Experience with Causal inference is a plus
- Experience with NLP is a plus
- Experience with working with FAIR data is a plus
- Experience with Responsible AI is a plus
- Experience with distributed machine learning is a plus
- Experience with Data Bricks is desired
- Experience in cloud-based development and deployment (Azure preferred)
Competencies:
- Creative and collaborative mindsets for find solutions to challenging business problems
- Translates complex technical solutions into business understanding.
- Creates solutions with the ability to continually prove accuracy and with a design goal of productization/ reusability.
- Talent development coupled with a flexible project management mindset to execute with flexibility in the face of shifting project and program situations.
- Stakeholder management is a must
- Presentation skills, both oral and written. Be able to explain data science results to a variety of audiences in several phases of projects
EEO Statement
All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, or disability status
PepsiCo is an Equal Opportunity Employer: Female / Minority / Disability / Protected Veteran / Sexual Orientation / Gender Identity
If you'd like more information about your EEO rights as an applicant under the law, please download the available EEO is the Law & EEO is the Law Supplement documents
View PepsiCo EEO Policy
Please view our Pay Transparency Statement