Overview
Location: Candidate must lives within 90 miles of one of the following locations: Plano, TX, Chicago, IL, Purchase, NY. Relocation is not offered for this role.
With data deeply embedded in our DNA, PepsiCo Data & Analytics 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 Pillar in D+A 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 D+A Products. And will support "pre-engagement" activities as requested and validated by the prioritization framework of D+A.
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Position Overview:
Senior Optimization Engineer
Your role will be to be part of growing team, 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 and analytics, where you will create and utilize prescriptive analytics to support the development of digital solutions to create business decision making, starting from the problem analysis and key data identification. 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. You will actively contribute to building a general-purpose optimization and simulation platform and you will create and solve mathematical optimization problems to answer critical business questions.
You will be an internal ambassador of the team's culture around data and analytics. You will provide stewardship to colleagues in the areas that you are an specialist or you are specializing.
#LI-HYBRID
Responsibilities
- Design, develop, implement, calibrate optimization and simulation models.
- Deploy optimization and simulation models as a service by leveraging cloud platforms.
- Develop source code and troubleshoot data issues and model solutions.
- Build complex datasets from multiple data sources.
- Work in coordination with IT to build data ingestion pipelines for optimal efficiency.
- Active contributor to code development in projects and services
- Act as contributor in innovation activities
- 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.
- Occasionally, coordinate work activities with Business teams, other IT services and as required.
- 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.
- Research in state-of-the-art methodologies.
- Create documentation for learnings and knowledge transfer.
- Create reusable packages or libraries.
Compensation and Benefits:
- The expected compensation range for this position is between $115,000 - $197,500 based on a full-time schedule.
- Location, confirmed job-related skills and experience will be considered in setting actual starting salary.
- Bonus based on performance and eligibility; target payout is 10% of annual salary paid out annually.
- 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
- Bachelor's or Master's degree in Operations Research, Industrial Engineering, Computer Science, Data Science, Statistics, Mathematics, or equivalent combination of education and experience
- Working knowledge in multiple optimization methods (LP, MILP, QCP, MIQP, CP etc.)
- Working knowledge in commercial optimization solvers (Gurobi, CPLEX, Xpress, etc.)
- Strong proficiency in Python and object oriented programming.
- Working knowledge of GIT, Linux/Unix and Bash/Shell scripting is preferred
- Working knowledge of statistical/machine learning tools preferred
- 4+ years' experience building solutions in the commercial or in the supply chain space.
- 4+ years working in a team to deliver production level analytic solutions. Business storytelling and communicating data insights in business consumable format.
- Working knowledge in model tuning/calibration
- Experience with Agile methodology for team work and analytics 'product' creation is a plus.
- Experience with Azure cloud services is a plus.
- Experience with working with FAIR data is a plus.
- Experience with Responsible AI is a plus.
- Strong written, oral communication, and interpersonal skills
- Strong project management, organizational, and prioritization skills with the ability to deal with ambiguity while juggling multiple priorities
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