Have a strong opinion about Tensorflow lacking an autoregressive dynamic network? So do we.
PepsiCo Data Scientist Position Opening
PepsiCo operates in an environment undergoing immense and rapid change, driven by eCommerce and emergent retail technologies. To ensure continued success in the food and beverage space, PepsiCo has assembled a dedicated eCommerce team – tasked with optimizing eCommerce operations and developing innovations that will give PepsiCo a sustainable competitive advantage. While tied closely to broader PepsiCo, the eCommerce group more closely resembles a start-up environment; embracing the core values of having bias for action, being results oriented, maintaining a community-focus, and prioritizing people.
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 does:
- Build machine learning systems to understand the cross-channel grocery ecosystem
- Lay the groundwork for reinforcement learning systems for eventual operations optimization
- 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
- Script using Python
- Stochastically optimize function approximators using Tensorflow
- (But we can read Theano, MxNet, Caffe, Chainer, PyTorch, etc code if needed)
- Optimize networks on a team server with 4 Tesla V100s (Nvidia’s new model with TPU cores)
- Store and access relational data in a SQL database
- Machine Learning expertise.
- Candidate should be comfortable designing and developing machine learning solutions to novel business problems using a variety of data sources.
- Candidate should have expertise with various complex modeling approaches; building on top of modern academic models such as ConvLSTMs, Adversarial Sampling, Neural Language Models, etc.
- Candidate should be able to propose custom solutions to business problems
- Excellent business communication.
- Candidate should be able to clearly and concisely express complex ideas to both technical and non-technical audiences.
- Candidate should be capable of outlining their approach to business problems in formal presentations forums and writing
- Passion for learning.
- Passionate about machine learning and actively following modern research
- Willing to experiment with different approaches and capable of applying new insights
- Educational Background
- Minimum BS in relevant field, experience with scripting, relational database access and optimization.
- Master’s degree completed no later than August 2019
- Minimum 1-3 years’ experience/familiarity with SQL and Python (Tensorflow experience preferred)
- Experience developing deep learning systems (software release experience preferred)
- Understanding of deep reinforcement learning systems
- Experience in market data science modeling and analysis. eCommerce / Digital space experience preferred
- Demonstrated problem solving skills
- Highly organized with careful attention to detail
- Ability to work and influence cross-functionally
- Excellent verbal and written communication skills, especially when talking about business implications of technical capabilities.
- Embodies entrepreneurial mindset and key values of having a bias for action, results-oriented, community-focused, and prioritization of people.