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
Catered lunch every day
Company outings and bi-annual offsites
Generous health insurance plan
Berkeley, CA
LeapYear is the world’s first platform for differentially private reporting, analytics and machine learning. We enable enterprises across highly regulated industries to safely create value from their most sensitive datasets.
The platform embeds mathematically proven privacy into every computation, statistic and model enabling analysts and data scientists to generate insights from data without exposing the data itself. Our customers safely leverage and share data across institutional silos, geographic borders and with third parties, all while preserving privacy and confidentiality.
LeapYear is deployed in production, at multi-petabyte scale, across global 1000 financial institutions, healthcare companies, and insurers.
The rise of large-scale data collection and machine learning has been accompanied by pressing questions related to privacy, security, and data access.
LeapYear builds technology to address these issues in a scalable, rigorous, and future-proof way.
With LeapYear, some of the largest enterprises in the world are able to break down data silos, form data partnerships, and accelerate the adoption of machine learning, all with mathematically proven privacy protection.