Snap One is a leading manufacturer and exclusive source of control, A/V, surveillance, networking, power, and infrastructure equipment for residential and commercial professionals. With a vast catalogue of today’s most popular brands, Snap One is the premier choice for professional installers across the globe. We believe that life’s better when everything works together, and the same can be said about the collaborative work we do. Join our award-winning team in our continuous quest to deliver the most brilliant, personalized smart living and smart business experiences to people around the world.
The Product Data Science team seeks a Data Scientist adept in Software and Data Engineering to leverage extensive data, and aid Snap One engineers in developing reliable, appealing products. The team acquires and assesses real-time device and platform data safely to support Snap One's design and development, utilizing software tools to orchestrate data analyses. The Product Data Science team uses data and data science to build new features and abilities into device and platform products, facilitated by automated data engineering tools that enable complex analysis of real-time tests and fleet devices.
In this role, you will work as a member of a fast-growing team, being involved in all steps of our MLOps pipeline. On a given day you may find yourself cleaning and embedding datasets, prototyping, tuning models, managing data drift, and planning out world-class solutions to novel and varied problems. Additionally, you will deliver analyses and presentations that will drive product design and improve customer lives.
- Participating in developing statistical and Machine Learning (ML) solutions to problems in varying domains (e.g. computer vision, dimension reduction, time series, regression, anomaly detection, audio, etc.)
- Develop relevant and impactful analyses, creating a deep understanding of our business, market, products, and customers
- Answer questions on fleet usage and behavior to enable proactive monitoring, grow reliability, and minimize field failure
- Adapt, learn, and grow to deliver world-class products and solutions
- Work closely with other product engineers to create/interpret/validate numeric models of fielded and in-test product
- Contribute to the automation and standardization of our MLOps pipelines, operations and build systems
- Build visualizations to communicate results effectively
- Bachelor's Degree and 3+ years of work experience in data science
- Experience developing and monitoring consumer-facing AI
- Experience in applying frequentist or Bayesian statistics to test hypotheses and judge confidence levels
- Experience with Tensorflow or Pytorch
- Experience in Python, SQL, and Git
- Demonstrable experience making highly informational, easily interpreted visualizations
- Effective communication
- Intermediate Degree in a quantitative field
- Experience with signal process or time series analysis
- Experience in Databricks
- Experience in PowerBI
- Work experience in IoT or ML at the edge
- Experience with MLOps
Snap One is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, or protected veteran status and will not be discriminated against on the basis of disability.