- DATA SCIENCE ENGINEER
- Unata - Toronto, ON
- What are we looking for? Unata is looking for an engineer to help scale our platform to support millions of shoppers across multiple retail partners around the globe. You’ll work with our team of developers and data scientists to build solutions that power slick mobile and web applications, personalized content services, and robust integrations with retailer data systems.
- TLDR; we want you to help us experiment, build and iterate on our machine learning technology while being a kickass engineer.
- Who are we? We are building the retail experience of the future. We work with large retailers to power their digital experiences, while personalizing each shopper’s content and offers based on their purchase history. We’re connecting the physical shopping experience with the best of the digital world.
- Unata’s digital marketing platform consists of state of the art data analysis systems, award-winning mobile and web applications, and machine learning technologies. We hold ourselves to the highest standards; our work has won awards from Apple and many industry publications.
- What makes working at Unata so great?
- Working with dedicated people that want to make an impact. This ain’t no another-day-another-dollar gig.
- A working environment where your opinions are discarded. Just kidding, your opinions are valuable. That’s why we want to hire you!
- A team that appreciates learning new technologies and implementing them when they make sense.
- Attending various developer conferences like PyCon where our team is regularly selected to present ( Latest tutorial )
- Competitive compensation and stock options.
- Stocked-up fridge full of food and beer.
- Totally-optional, totally-fun activities every Friday, usually ping pong at Spin Toronto or board games in the office.
- Requirements, requirements, requirements
- Solid grasp of computer science concepts: data structures, algorithms, and programming paradigms. We are very keen on implementing red-black trees here at Unata.
- Excellent understanding of machine learning systems.
- Understands and implements engineering best practices: automated testing, version control systems, documentation, continuous integration, duct tape redundancy, etc.
- Feels at home (cd ~) in a Unix development environment.
- Can clearly communicate complex technical concepts.
- Has built and shipped real software. You know… flappy bird clones… all that jazz.
- Can demonstrate and talk about their willingness to learn new things. Like that new reactive microservice framework everyone’s been deploying on docker lately.
- BONUS POINTS!
- Degree in Machine Learning, Software Engineering, Computer Science, etc.
- Experience in Machine Learning and Statistics
- Familiarity with the academic literature on Recommendation Systems
- Experience with the following technologies (C-c-c-c-Combo Breaker!):
- Python (+ for Flask, SQLAlchemy, Celery)
- RDBMS (+ for PostgreSQL)
- Cassandra
- Memcached
- Redis
- Cool personal projects on github or other places
- Oh! And a willingness to be the greatest ping pong player in the world (or the office
http://ca.indeed.com/viewjob?jk=c7b56a76627043c5&q=Machine+Learning&l=Toronto%2C+ON&tk=1aqsuftc7aeuiace&from=web
发帖
雷达卡
京公网安备 11010802022788号
