Data Engineer - Machine Learning (Austin or Houston or Remote) at Cart.com (Austin, TX)
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Cart.com is an ecommerce software, services, and brand holding company on a mission to democratize ecommerce and give digital merchants the freedom to grow. We are integrating all the pieces of the ecommerce value chain brands need to thrive, creating a truly end-to-end Ecommerce-as-a-Service platform that helps third party brands (and a few of our own) move faster, grow more quickly, and deliver on their promises more completely.
The data science team at Cart.com is a centralized team that reports directly to the CEO and is responsible for all things data, analytics, and ML/AI of Cart.com. The team consists of Cloud Architects, Data Engineers, Software Engineers, Data Scientists, ML Engineers, and Data Viz specialists. It is our team's mission to disrupt longstanding players in the value chain of ecommerce by designing a distributed network of capabilities that are 10x cheaper, 10x more convenient, and 10x better.
- Engineer data products to be used by the various services of the Cart.com platform - including but not limited to the domains of marketing, merchandising, site personalization, logistics, and supply chain
- Step in and execute all components of the data life cycle, when needed - design, develop, evaluate, deploy, serve, monitor, and maintain
- Partner with cloud architects and ML engineers to design any and all requirements that are needed for ML products
- Heavy usage of Python and other capabilities, as needed, in order to develop products that are robust and scale to the thousands of current customers within the Cart.com ecosystem
- Help in the contribution and construction of the product roadmap including design and testing of POC products
- Push the boundaries of what is believed to be possible with respect to personal growth and technology to ensure the success of our team and the customers of Cart.com
- Provide, promote, and accept feedback and guidance (from all levels) to promote a culture of continuous improvement, collaboration, and shared knowledge within a geographically dispersed and cross-functional team
- 2+ years of relevant experience
- Experience with retail and/or e-commerce - preferred
- Proven experience in programming languages, namely Python - preferred
- Familiarity supporting data science teams - preferred
- Familiarity with the deployment of data products inside production environments
- Experience leveraging CI/CD
- Solid understanding of Git and its proper usage within a decentralized software development team
- Bachelor's / Master’s / PhD degree in STEM - preferred but not required
OUR CORE VALUES:
These aren’t just buried somewhere in an employee manual. We live and breathe them. They are on the walls and live in our hearts. They come up constantly in conversations and actions. They govern the decisions of the newest hire all the way up to our CEO:
WE ARE OBSESSED WITH BRANDS
We live for brands and are fanatical about their success.
WE THINK BEYOND THE BOX
We explore new ideas and discover creative solutions. We think openly about how to serve brands and solve problems.
WE DON'T GIVE UP
No one expected this to be easy. We are resilient— we dig in and keep going.
WE SPEAK UP
Every person here has an obligation to question norms, voice concerns, and offer their perspective.
WE WORK TOGETHER
We work with integrity and respect, ask for help, and extend the same help to others.
WE ARE HUMAN
Our people are our biggest strength. We have fun and make real connections with one another and with the brands we serve.
Cart.com is deeply committed to building a diverse and inclusive workplace. We’re proud to be an equal opportunity employer, seeking to identify and onboard people from all walks of life. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, family status, marital status, sexual orientation, national origin, genetics, neurodiversity, disability, age, or veteran status, or any other non-merit based or legally protected grounds.
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