LeapYear Technologies
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about 2 years ago
LeapYears secure data platform is deployed by some of the largest enterprises in the world across finance, healthcare, and technology.
Our technology ensures differential privacy, a widely recognized standard of data privacy that enables all data - including sensitive information - to be utilized for analytics, while providing mathematically proven privacy protection.
Our Algorithms team is at the forefront of our efforts to apply differential privacy to real-world problems. We take exciting, cutting-edge ideas from the research community and develop novel implementations that enable our customers and partners to do incredible things with sensitive data.
We work in Python, Haskell, and Scala to develop these algorithms, closely partnered with domain experts as well as the rest of the engineering organization. In the past, we’ve produced everything from Python-based experiments, to safety and performance-critical distributed implementations in Haskell and Scala/Spark.
Our ideal team-mate is someone who loves learning and teaching. We’re challenged to stay current with both the latest research in privacy-preserving technologies, as well as thinking about how to apply and explain those ideas effectively to the complicated worlds of our users and customers.
Responsibilities
- Design and implement novel privacy-preserving algorithms.
- Work closely with domain experts to uncover new applications of differential privacy.
- Develop sustainable and extendable software systems.
- Plan, implement, and optimize new features from idea to release.
Requirements
- 3+ years of industry experience.
- PhD, or equivalent experience, in a field involving the application of advanced mathematics (computer science, statistics, math, physics, electrical/systems engineering)
- Exposure to functional programming concepts and languages.
- Strong foundation in data structures, algorithms, and software design.
- A love of learning and teaching.
- A track-record of project ownership and delivery (either academic or professional).
Nice to Have
- Familiarity with differential privacy theory and implementation.
- Familiarity with other privacy-preserving technologies.
- Professional experience with functional programming languages.
A Few of the Perks
- Culture of teaching and learning
- Competitive compensation package of salary and equity: $150,000 – $250,000, depending on skills and experience
- Matching 401k plan
- Generous health insurance plan
- Disability, accident, and life insurance
- Relocation support
- Company outings
- Build your ideal work station