The Data Science team at RetailMeNot work on initiatives that enable us to provide users meaningful content at the right place, right time, and right price. We build, test and iterate on Machine Learning models, learning from and leveraging datasets with millions of daily visits. We are looking for software engineers who are not afraid of learning new technologies, have an itch or have been playing around with Machine Learning, and are ready to apply it to solve real and meaningful business problems.
As part of the Data Science team you will work together with software engineers, data scientists and data engineers leveraging the latest technology and bringing new ideas to the table and building the world’s largest savings destination. Our teams challenge each other to have fun while connecting shoppers to the brands they love. Some of the technologies that we use today include AWS (EMR), Spark, Docker, Luigi.
This team is integral to the RetailMeNot business, so we need engineers who can deliver results while understanding the structure of a large system. We provide cross-team leadership that ensures that RetailMeNot code meets a consistently high standard while building the platform to support the future of the company. Your daily activities will involve oversight, mentoring, delivering key pieces of functionality, and collaborating with technology leadership to plan the technical roadmap for RMN.
We are constantly evolving both the software and the teams that deliver it. If you’re someone who enjoys taking on new challenges, working in a rapidly changing environment, learning new skills, and applying it all to solve large and impactful business problems, then we want you to be a part of the team!
RetailMeNot is headquartered in Austin, TX! This position is fully remote and we encourage applicants nationwide!
Who You Are
- Have a Bachelor's degree in computer science or equivalent STEM field, or equivalent work experience
- Have 3+ years of experience in software development, preferably in a data science or data team
- Are proficient in Python or Scala and have some experience in big data technologies like Spark
- Have experience with different DAG schedulers (Luigi, Airflow etc.) and cloud platforms (AWS and/or GCP)
- Are comfortable with container-based technologies like Kubernetes and Docker
- Strive to identify simple solutions to complex problems - can identify a minimal viable product and enjoy iterative development
- Are excited by the opportunity to direct themselves and work independently to solve larger goals
- Data science/Machine learning knowledge is a plus
What You'll Do
- Design, develop, and own production services to support scalable offline machine-learning pipelines and online components
- Build feature and data pipelines for different machine learning projects
- Research and recommend new technologies/frameworks for infrastructure improvements like managing lifecycle of ML models etc.
- Research and test out MVPs to identify new opportunities for the company
- Work together with your agile team to improve process and delivery through collaborative problem-solving
- Cultivate and enhance a culture built around standard methodologies for CI/CD, alerting, and monitoring
Who We Are
- We have an open environment where engineers are given a lot of responsibility and the freedom to make a huge impact.
- We have lots of smart people to work with and learn from.
- We work on large scale challenges with a variety of technologies and believe in an ever-growing diversity of technology platforms.
- We believe in giving prizes, bonuses, and recognition for doing what you enjoy.
Let us know
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