Job Description

The Problem

Every data-driven industry - healthcare, financial services, technology, telecommunications, insurance - holds highly valuable datasets that are underleveraged due to privacy, security, and regulatory concerns. 

The Product

LeapYear develops technology to solve this problem for the enterprise. The company has combined over a decade of research and hundreds of academic papers in advanced cryptography to develop a privacy-preserving platform for reporting, analytics, and machine learning. The product allows insights to be generated from sensitive datasets without exposing the underlying data. 
Today, organizations use LeapYear’s technology to generate new business from previously inaccessible datasets - the platform is powering use cases including cross-border data sharing, cross-LOB data access, and third-party data commercialization.

The Team

LeapYear’s go-to-market team includes:

- solutions architects and data scientists with prior experience at Palantir, Citi, Amex, EY, Harvard, and BCG
- sales executives with deep domain expertise in financial services, healthcare, data commercialization, information security, and European markets.  
If you are interested in interviewing for this position, please submit an application below.

Responsibilities

Develop a deep understanding of data privacy, security, and machine learning, from a business, technology, and policy perspective 
Become an expert in applying LeapYear's technology to complex enterprise problems
As a technical subject matter expert, educate customers, prospects, and partners on differential privacy at mathematical level, and help translate its impact into business value
Alongside a sales director, execute a use-case driven land-and-expand strategy, and build existing accounts by discovering new use cases across Global 2000 enterprises
Serve as an active customer advocate in product management discussions, especially feature prioritization and defining requirements

Qualifications

Ability to present complex technical concepts in a clear, precise, and actionable manner with excellent interpersonal, written, and verbal communication skills 
Fluency in data analytics architecture, including knowledge of Big Data (e.g. Hadoop/Spark ecosystem), RDBMS, ETL concepts, BI tools, advanced machine learning (e.g. scikit-learn, MLlib, TensorFlow), etc.
Familiarity with data science process, machine learning, data architecture, and IT systems
Demonstrated ability to build and manage enterprise customer relationships
Experience communicating with diverse audiences, including but not limited to line-of-business, technical, and executive stakeholders
Prior experience positioning the value of data science from business and technical standpoint
Undergraduate or graduate degree in relevant technical discipline, such as CS or math
Experience with the analytical workflows used in financial services and healthcare
Ability to coordinate with engineering, product management, marketing, and data science teams
Entrepreneurial mindset & demonstrated success in a dynamic start-up environment

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
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