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PepsiCo

Senior Data Scientist

PepsiCo

H1B ✓Hybridsenior levelPosted March 27, 2026

About the Role

The Senior Data Scientist will be responsible for leading and delivering large-scale data analytics and machine learning initiatives, including designing, building, deploying, and maintaining scalable ML models and data pipelines in production. This role also involves collaborating cross-functionally to analyze large datasets, establish best practices for ML code, and provide technical thought leadership.

Requirements

Candidates must possess a Master’s Degree in a quantitative field like Data Science, Computer Science, or Statistics, along with a minimum of 3 years of relevant professional experience in data science or machine learning. Essential qualifications include strong Python skills, experience with deep learning frameworks, and a solid foundation in statistical modeling.

Full Job Description

Overview

We’re seeking a Senior Data Scientist to build and scale machine learning solutions that drive high-impact business outcomes. This role partners closely with business and technology teams to deliver advanced analytics, production ML systems, and data-driven insights supporting our global Strategy and Transformation agenda.


Responsibilities

  • Lead and deliver large-scale data analytics and machine learning initiatives
  • Design, build, deploy, and maintain scalable ML models and data pipelines in production
  • Collaborate with cross-functional teams to analyze large datasets and develop custom models that uncover actionable insights
  • Establish best practices for clean, maintainable, and production-ready ML code
  • Provide technical thought leadership and support data-driven decision-making across the organization
  • Communicate results, trade-offs, and impact to both technical and business stakeholders

Qualifications

  • Master’s Degree in Data Science, Computer Science, Statistics, or equivalent
  • 3+ years of relevant professional experience in data science or machine learning
  • Proven experience designing and delivering ML solutions using diverse data sources
  • Strong Python programming skills and solid software/data engineering fundamentals
  • Experience with deep learning frameworks such as TensorFlow or PyTorch
  • Strong foundation in statistical and mathematical modeling
  • Experience with cloud-based and distributed computing platforms
  • Working knowledge of Generative AI technologies, including LLMs, prompt engineering, and RAG architectures
  • Ability to clearly communicate complex technical concepts to diverse audiences

 

What makes us different?  

  • Hybrid work model: combination of remote and collaborative office experience to enable innovation
  • Entrepreneurial environment in leading international company
  • Professional growth possibilities & learning opportunities
  • Variety of benefits to support your physical, emotional and financial wellbeing
  • Volunteering opportunities to help external communities
     
    About PepsiCo  
     
    We believe that culture should be at the cornerstone of everything we do at PepsiCo. We are agile, innovative and not afraid of failure. We want our team to come to work every day excited to explore new ways to bring enjoyment, refreshment and fun to the world. 
    PepsiCo Positive (pep+) is the future of our organization – a strategic end-to-end transformation, with sustainability at the center of how we will create growth and value by operating within planetary boundaries and inspiring positive change for the planet and people. 
    So, if you’re ready to be a part of a playground for those who think big, we’d love to chat. 
     

*We encourage the diversity of applicants across gender, age, ethnicity, nationality, sexual orientation, social background, religion or belief and disability.

 

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Compensation

AI Est. Total Comp

$162,000

Details

Location

Albuquerque

Work Type

Hybrid

Seniority

senior level

Experience

2-5 years

Category

core ds

Quality Score

5.8

Key Skills

Machine LearningData AnalyticsPython ProgrammingModel DeploymentData PipelinesTensorFlowPyTorchStatistical ModelingMathematical ModelingCloud ComputingDistributed ComputingGenerative AiLlmsPrompt EngineeringRag ArchitecturesCommunication