Job details
Job type full-time
Full job description
At shipt, we are transforming the grocery shopping experience and giving time back to consumersShipt shoppers handpick fresh groceries and household essentials, then deliver them to your door in as little as one hour.
Shipt is building an on-demand delivery platform to help people get the things they need from stores they loveSince the beginning, we’ve relied on data to drive decision-making and power our fulfillment systemIn this role, you’ll help build the next generation of processes and algorithms to drive our platform to new heights.
You will be building next generation systems that leverage cutting edge technology and advanced mathematics to build a best-in-class system to optimize orders, match them to our shoppers, and offer them in a way that helps our shoppers achieve their goals while maintaining strong customer outcomes.
This is a role where you will be building technology that leverages advanced mathematics, working side by side with other technologist to deploy your models directly to the heart of our ecosystem.
The ideal candidate will have a deep passion for mathematics and a desire to see mathematical solutions deployed against large scale problemsWe are seeking candidates who are excited about wearing multiple hats and working cross-functionally with engineering and product to bring real solutions to market on short timelines, iterating from imperfect mvp through rapid experimentation and development.
Responsibilities
Develop a deep understanding of shipt’s business model and leverage your experience to align our problems with industry best solutions.
Design and implement core algorithms that drive our platform, owning their performance in production and continually evolving these services to deliver better outcomes over time.
Help increase the speed and confidence at which shipt can make and execute on data-driven decisions through the development of simulation, experimentation, and testing environments.
Requirements
3+ years of experience solving large-scale optimization problems in marketplace, logistics, or supply chain settings.
2+ years of experience with machine learning and/or statistical modeling.
Familiarity with linear & nonlinear optimization as well as mixed integer & constraint programming.
Familiarity with core applied use cases of optimization in the field of operations research, including routing, assignment, scheduling & flow.
Proficiency with one high level language, such as python.
Master’s degree in industrial engineering, operations research, mathematics, or related experience with mathematical optimization.
Nice-to-haves
Familiarity with cloud computing platforms like aws, gcp, or azure.
Familiarity with containerization technology such as docker or kubernetes.
Familiarity with software engineering practices and technologies like system design, unit testing, and version control.
Familiarity with streaming systems such as kafka.
Familiarity solving vehicle routing problems and working with routing technology like osrm, valhalla, graphhopper, etc.
Familiarity with on-demand and multi-sided marketplaces.
Phd with relevant applied research is a plus and would be considered as part of years of experience.
This position can be 100% remote#li-remote
We are an equal opportunity employer and value diversity at our companyWe do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
Pursuant to the san francisco fair chance ordinance, we will consider for employment qualified applicants with arrest and conviction records.
