Sysco LABS is a technology-focused division within Sysco, dedicated to reimagining foodservice through innovation. An extension of Sysco’s commitment to deliver exceptional products and services to the foodservice industry, Sysco LABS uses customer and market intelligence, data-driven insights and agile technology development to rethink the entire foodservice ecosystem.
Our innovation will improve everything from the ordering process, inventory, pricing and automation to the in-restaurant customer experience. Operating with the mindset of a startup and backed by the authoritative expertise of an industry leader, Sysco LABS’ mission is to improve the Sysco customer experience and consistently deliver cost savings and new innovations through technology.
About the Role
This role will apply advanced analytics to support the evaluation and development of new search recommendation engines, notification models and algorithms. This will require expertise in mathematical modeling, analytical and heuristic solution methods, the ability to synthesize, visualize and communicate the result, and the ability to work with production engineering teams to turn the solution into a deployable form. This role will require close collaboration with other functions within the CX Analytics Team and Commercial Technology in addition to other functions within Sysco.
- Work cross-functionally with other roles within the CX Analytics Team, Commercial Technology, and Sysco broadly to tune models and ensure value created from models.
- Collaborate with business process owners to validate model outputs and construct an appropriate training
- Design final model architecture with a production environment in mind; Work with Shop Engineering teams to maintain best practices for up time, integration, and robust ness
- Support models in the deployed production environment
- Lead development of production-ready models for delivery windows, product recommendations, inventory availability, search relevance optimization, customer segmentation, feature personalization, frequentist and Bayesian inference for experimentation, etc.
- Work directly with product management to identify and frame business problems that will likely respond to quantitative methods.
- Develop and test search relevancy models
- Offline search testing infrastructure design and implementation in collaboration with the data engineering team
- Collaborate with the search feature team to guide and conduct offline and online experiments
- Speed online and offline experiment cycle times through automated reporting and analysis tools.
- Support data analysts with statistical expertise, especially as relates to experimentation
- Communicate methodologies and results to less- and non-technical audiences.
- Master’s or Ph.D. degree in Computer Science, Engineering, Mathematics, Statistics, Neuroscience or another technical field with a focus on quantitative research OR
- Bachelors with 18 months+ of relevant job experience
- 4+ years of experience accessing and manipulating data in SQL or NoSQL database environments
- 2+ years of experience with scientific scripting languages (e.g., Python, R, SAS) and/or object-oriented programming (e.g., C++, Java)
- 3+ years of experience with Bayesian statistics, regression analysis (beyond linear regression), supervised learning, unsupervised learning or time-series analysis required
- 5+ years of overall analytics experience, can be inclusive of post-graduate work
- Experience with event data, AWS cloud infrastructure, S3 data lake with a Presto/Athena interface, and Optimizely’s online testing platform preferred