APIs form the foundation of the application innovation needed to drive business success today. Across banks, retail and transportation, IoT, autonomous vehicles, and smart cities, every web and mobile app depends on APIs. Without secure APIs, businesses cannot rapidly innovate. Salt Security has delivered the only patented solution to identify and prevent API attacks, using Big Data and AI to thwart this top threat to businesses today.
Who We are
At Salt, we’re passionate about what we do. We work as a team and embrace new ideas, wherever they come from. We also enjoy all the benefits of a startup environment, including quickly seeing the results of your work, making an outsized impact on our company, and solving a diverse set of engineering challenges.
Want to make a big difference? We encourage you to apply!
About the position
Our research team deals with the extremely challenging aspects of Salt’s cutting edge solution. From inventing and validating new algorithms to delivering advanced insights and analytics, we use our data to level up the security we provide to our customers.
Anomaly detection, classification, prioritization and complex graph analysis problems are our bread and butter. Building advanced ML pipelines alongside keeping our models and algorithms at the state of the art is our continuous challenge. Together with our super talented engineering team, we set the industry bar for AI based API security.
We are looking for a passionate data scientist to help our growing data science team to face the biggest challenges in the fields of API attacks detection and prevention.
To learn more about Salt Security’s R&D – https://tinyurl.com/salt-rnd
Who are you?
- MSc/PhD in computer science, math, physics or related field
- 2+ years of experience as a data scientist/data engineer
- Strong theoretical grounding in core machine learning concepts and techniques
- Proficiency with a variety of modern machine learning methods (decision trees based schemes, clustering methods, statistical graph analysis etc)
- Experience with statistical and machine learning tools and frameworks – Python, Spark etc.
- Self-learner, initiator, able to quickly learn new technologies
- Experience in working with engineering teams to deploy models in production grade systems, evaluating and improving models based on engineers and customers feedback
- Experience with data pipelines / big-data analytics – advantage