PepsiCo’s Data Science and Analytics group is a team of data scientists, technology specialists, and business innovators who operate within eCommerce to build industry-leading systems and solutions. By focusing on machine learning and automation, the Data Science & Analytics group is pushing the bounds of possibility for PepsiCo and its strategic partners.
What PepsiCo Data Science & Analytics Does
- Build machine learning systems to understand the cross-channel grocery ecosystem
- Perform statistical analysis across diverse datasets to drive and measure performance
- Work with PepsiCo’s strategic partners to expand their technical capabilities, thereby creating a more robust data environment
- Utilize natural language understanding techniques to uncover insights from contextual data
- Develop scalable tools to drive automation and optimize business operations
As a Principal Data Scientist, you will play a critical role in shaping and executing the global eCommerce growth agenda. You will be tasked with identifying, designing, and implementing data science/machine learning solutions to business problems. You will collaborate with the larger data science and analytics teams to create a robust, shared codebase; on which PepsiCo will build automated eCommerce systems. You will work with internal business stakeholders and strategic partners to identify opportunities for collaborative development and foster a data-driven culture between relevant teams.
Responsibilities
- Work with the larger eCommerce organization to analyze large data sets and develop custom models/algorithms to uncover trends, patterns, and insights
- Stochastically optimize using Tensorflow and PyTorch; Compute on a team server with 4 Tesla V100s (Nvidia’s new model with TPU cores)
- Establish standards for writing clean, organized machine learning code to streamline machine learning workflow within the DSA team
- Provide critical thought leadership to enhance organizational capabilities by utilizing a variety of data sets; work with business stakeholders to identify and execute on opportunities for enhancement
- Partner with other analytics leaders within PepsiCo to foster enhanced analytical capabilities globally
Qualifications/Requirements
- Master’s Degree in Data Science or equivalent
- Minimum 5 years of relevant work experience
- Experience designing and developing machine learning solutions using a variety of data sources
- Expertise customizing Modern ML systems, including NLP, Deep RL, and/or Graph Neural Networks.
- Experience and functional familiarity with software development and data engineering best practices
- Expertise designing custom deep learning systems using Tensorflow or Pytorch
- Expert in mathematical models underlying data science methods, understanding the trade-offs between different solutions
- Demonstrated ability to effectively and concisely communicate with both business and technical audiences
Relocation Eligible: Not Applicable
Job Type: Regular
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
Their Company will consider for employment qualified applicants with criminal histories in a manner consistent with the requirements of the Fair Credit Reporting Act, and all other applicable laws, including but not limited to, San Francisco Police Code Sections 4901 – 4919, commonly referred to as the San Francisco Fair Chance Ordinance; and Chapter XVII, Article 9 of the Los Angeles Municipal Code, commonly referred to as the Fair Chance Initiative for Hiring Ordinance.
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
More Information
- Salary Offer 0 ~ $3000
- Experience Level Junior
- Total Years Experience 0-5
- Dropdown field Option 1