BI / Analytics / Data
Ring is looking for an Applied Scientist, to join a new project team working to build a ground breaking product. Our organization rewards intellectual curiosity while maintaining the direct to market product focus. Our mission is to invent and simplify large-scale solutions and bring the future to Amazon customers.
As an applied scientist, you will be using Amazon’s large-scale computing resources to build models describing best suited recommendations and work with domain experts and engineers to turn those models into production solutions. You will participate in the Amazon ML community and partner with software development engineers with a strong interest in and knowledge of ML. Your work will directly benefit customers. We are looking for passionate, hard-working, and talented Applied Scientist who has experience building mission critical, high volume applications that customers love. You will have an enormous opportunity to make a large impact on the design, architecture, and implementation of cutting edge products used every day, by people you know.
- Use machine learning and analytical techniques to create scalable solutions for business problems
- Analyze and extract relevant information from large amounts of data to perform feature engineering
- Design, development and evaluation of generalized ML models
- Work closely with software engineering teams to drive real-time model implementations and new feature creations.
- Work closely with business stakeholders to identify opportunities of current model improvements and new models to significantly benefit the business bottom-line
- Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation
- Research and implement novel machine learning and statistical approaches
- MS in Computer Science, Machine Learning, Operational Research, Statistics or a related quantitative field
- 4+ years of practical experience applying ML to solve complex problems
- 3+ Experience using Java, C++, or other programming language, as well as with R, MATLAB, Python or similar scripting language
- Experience distilling informal customer requirements into problem definitions, dealing with ambiguity and competing objectives
- Experience delivering systems into production with high precision
- The ideal candidate will have a PhD in Mathematics, Statistics, Machine Learning, or a related quantitative field
- 5+ years of relevant work experience
- Expertise on a broad set of ML approaches and techniques, ranging from Artificial Neural Networks to Bayesian Non-Parametric's methods.
- Expert in more than one more major programming languages (C++, Java, or similar) and at least one scripting language (Perl, Python, or similar).
- Strong fundamentals in problem solving, algorithm design and complexity analysis.
- Strong personal interest in learning, researching, and creating new technologies with high commercial impact.
- Extensive practical experience in several of the following areas: Natural Language Processing, Recommendation Systems, Clustering techniques
- Ability to handle multiple competing priorities in a fast-paced environment
- Superior verbal and written communication and presentation skills, ability to convey rigorous mathematical concepts and considerations to non-experts.
Ring's mission is to reduce crime in neighborhoods by creating a Ring of Security around homes and communities with its suite of home security products and services. The Ring product line, along with the Ring Neighbors app, enable Ring to offer affordable, complete, proactive home and neighborhood security in a way no other company has before. In fact, two Newark, NJ neighborhoods saw an over 50 percent decrease in home break-ins after Ring Video Doorbells and Spotlight Cams were installed on 11% of homes in the communities from April-July 2018 when compared to the same time period in 2017. Ring is an Amazon company. For more information, visit www.ring.com. With Ring, you’re always home.
Ring LLC is proud to be an equal opportunity employer and provides equal employment opportunities (EEO) to all employees and applicants without regard to race, color, religion, sex, national origin, age, disability, veteran status, sexual orientation, gender identity or genetics.