Sr. Data Scientist
About Spring Labs:
Spring Labs is redefining how data is exchanged for the new age of data sharing, security, and consumer privacy through decentralization. Our Spring Protocol Tech Stack, which includes the use of Blockchain and Cryptography, allows institutions to share information among themselves to verify identities and reduce fraud - all while protecting consumer data.
Working at Spring Labs is about being part of a collaborative team, comprised of some of the most talented people in the industry. You would be welcomed into a fun, inclusive environment where we care as much about our employees as we do about our product.
At Spring Labs, Sr. Data Scientists assist with the development and implementation of our data product portfolio. You will work closely with the Product and Engineering teams to help conceptualize, build, deploy and maintain a portfolio of data products powered by advanced ML techniques in order to solve real world use cases for the Financial Services Industry.
Outside of Covid, Spring Labs is an in office team.
What you'll do
- Work with product team to document use cases and develop data driven approaches to solve those use casesIdentify and evaluate data features from a variety of structured and unstructured data sources
- Build model prototypes to prove data value and use case fit
- Create requirement documents by engaging with multiple stakeholders to ensure all functional and technical requirements are met within legal & compliance constraints
- Work with engineering teams to build scalable data pipelines that can support precompute of complex data features as well as real time scoring of ML based models that feeds production API
- Develop test and ongoing monitoring plans to ensure data features and models perform as expected in both QA and production environments
- Help troubleshoot data product issues and optimize data systems
- Provide subject matter expertise to educate both internal stakeholders and external partners on modeling concepts
About you
- Bachelor’s degree in Computer Science, Engineering, Mathematics, Statistics or a related quantitative field preferred
- 5+ years of hands-on experience in Credit Risk Modeling, Applied Machine Learning, Statistical Analysis
- 3+ years in the Financial Services, FinTech or related Industry strongly preferred
- Highly proficient in Python, R, SQL, Spark, and other big data tools
- Expertise in statistical and machine learning techniques such as Logistic Regression, Tree based ML algorithms (Random Forest, XGB), Deep Learning, Natural Language Processing
- Ability to present at all levels of an organization, both internally and externally
- Extensive experience communicating key points through data visualization
- Understanding of regulatory requirements for models in Financial Services is a plus
- Curious learner staying on top of latest developments in modeling practices, algorithms and ecosystems
- Ability to self manage, while producing quality work in a collaborative environmentAdvanced troubleshooting skills
Perks
- Casual Work Environment
- Fully Stocked Kitchen
- Free Gym
- Weekly Office Events
- Flexible PTO
- Paid Sick Leave
- Comprehensive Medical/Dental/Vision
- 401(k)
Equal Opportunity Statement:
We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.