LeapYear: Lead Data Scientist
Seeking a Lead Data Scientist, responsible for conceptualizing, developing, testing, and deploying machine learning products on customer data sets. You and our data science team will use LeapYear's platform to create value from the world's most sensitive, siloed data sources.
Thanks for your interest in working at LeapYear.
This is an overview of the problem we are solving, what we’ve done so far, and how you can get involved.
LeapYear has developed the first secure machine learning platform. We have partnered with the world's leading healthcare and financial services companies, raised $12.6M in capital, and built a team of researchers, engineers, and advisors who are world experts in the intersection of cryptography and machine learning.
Advances in machine learning enable enterprises to deploy massive amounts of data towards valuable predictions, decisions, and data products.
However, in regulated industries, the progress towards building intelligent systems is limited by security and privacy concerns. No meaningful security exists for data while it is being accessed by authorized analysts and applications, and the performance of intelligence systems degrades as access to information is restricted. Current methods, such as encryption, hashing, tokenization, and anonymization limit data access, and are easily defeated by attackers.
As a consequence, hundreds of millions of sensitive records are breached each year, and enterprises must make costly trade-offs between the security and utility of their data assets.
LeapYear has applied the latest research in cryptography and machine learning to create a new approach to the problem of information security.
We have built the first data science platform that protects data during use. LeapYear’s technology enables machine learning and advanced analytics on sensitive data with proven assurances of security and privacy.
LeapYear's team has decades of collective experience with Google, Apple, the Department of Defense, and includes PhD-level cryptographers and machine learning researchers from MIT, Stanford, Cambridge University, and Microsoft Research. We have a strong culture of teaching, learning, and constant improvement.
To learn more about our mission, team, and company culture, please see: http://leapyear.io/careers
As a data scientist at LeapYear, you will be responsible for conceptualizing, developing, testing, and deploying machine learning products on customer data sets. You and our data science team will use LeapYear's platform to create value from the world's most sensitive, siloed data sources.
For details on the specific responsibilities and requirements of this role, please see below.
- Leverage LeapYear’s secure machine learning platform to deliver value from the world’s most sensitive and previously siloed data sources
- Conceptualize, develop, test, and deploy machine learning products on customer data sets using LeapYear’s platform
- Become an expert user and advocate of LeapYear’s secure machine learning SDK and collaborate with product and engineering to develop best practices and new features
- Serve as a technical and subject matter expert in financial services and healthcare information technology, assisting sales during pre-sales and post-sales efforts
- PhD or equivalent in machine learning, computer science, math, statistics, or physics
- Strong foundations in the theoretical underpinnings of machine learning
- Minimum 2 years of data science experience required
- Experience manipulating and analyzing complex, high-volume, high-dimensionality data from varying sources
- Ability to communicate complex quantitative analysis in a clear, precise, and actionable manner
- Experience working with large data sets and tools like MapReduce, Hadoop, Hive, etc.
- Experience working with large data streaming technologies like Spark, Flink, etc.
- Ability to work both independently and collaboratively in a fast-paced startup environment
- Expert knowledge of data analytics architecture, including knowledge of RDBMS, ETL, BI, and advanced machine learning libraries (e.g. Scikit-learn, MLlib, TensorFlow, Theano, Caffe), etc.
- Deep understanding of data science process, machine learning, data architecture, and IT systems
- Experience with the analytical workflows used in financial services and healthcare
A few of the perks:
- Culture of teaching and learning
- Competitive compensation package of salary and equity
- Catered lunch and dinner every day
- Company outings
- Build your ideal work station
- Generous health insurance plan
- Free yoga and meditation classes at a world-class studio downstairs
- Relocation support
Our team solves hard, real-world problems that impact every data-driven organization.
We are looking for more people that thrive in an open environment working on deeply technical challenges.
If you are interested in interviewing for this position, please submit an application below. Thanks for your consideration.