Director of Solutions Architecture
LeapYear Technologies
IT
Remote · United States
Posted on Thursday, May 7, 2020
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
- Build your ideal work station