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.
To learn more about LeapYear's mission and values, visit leapyear.ai/careers.
For details on the specific responsibilities and requirements of this role, please see below.
- Leverage LeapYears secure machine learning platform to deliver value from the worlds most sensitive and previously siloed data sources
- Conceptualize, develop, test, and deploy machine learning products on customer data sets using LeapYears platform
- Become an expert user and advocate of LeapYears 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
- Company outings
- Build your ideal work station
- Generous health insurance plan