Model Risk Data Scientist

SentiLink provides innovative identity and risk solutions, empowering institutions and individuals to transaction with confidence. We’re building the future of identity verification in the United States replacing a clunky, ineffective, and expensive status quo with solutions that are 10x faster, smarter, and more accurate.

We’ve seen tremendous traction and are growing extremely quickly. Our real-time APIs have helped verify hundreds of millions of identities, starting with financial services and rapidly expanding into new markets. SentiLink is backed by world-class investors including Craft Ventures, Andreessen Horowitz, NYCA, and Max Levchin.

We’ve earned recognition from TechCrunch, CNBC, Bloomberg, Forbes, Business Insider, PYMNTS, American Banker, LendIt, and have been named to the Forbes Fintech 50 list every year since 2023. Last but not least, we’ve even made history -– we were the first company to go live with the eCBSV and testified before the United States House of Representatives on the future of identity.

SentiLink supports a variety of ways to work, ranging from fully remote to in-office. We operate as a digital-first company with strong collaboration across the U.S. and India. We maintain physical offices in Austin, San Francisco, New York City, Seattle, Los Angeles, and Chicago in the U.S., and in Gurugram (Delhi) and Bengaluru in India. If you’re located near one of these offices, we would love for you to spend time in the office regularly. Some roles are hybrid or in-office by design. For example, our engineering team in India works primarily from our Gurugram office.

This is a remote, US-based role.
Responsibilities: 

• Build out our foundational processes for generating and surfacing model performance metrics, including crafting + calculating the metrics and building python rails.

• Act as point of contact for Strategic Financial Partners and manage their model governance needs. Regularly conduct performance and exploratory analyses to establish the quality of model outcomes.

• Providing guidance on the appropriate use of our products, respond to inquiries around model development procedures and generate stability analyses.

• Create automation to detect inconsistencies or issues with the production models that power our fraud detection products, such as data driven gap analysis to automation via anomaly detection or training challenger models to identify weaknesses.

• Primarily work with a Python ecosystem, using SQL, SageMaker, S3, Metabase and Git to support.

Requirements: 

• Bachelor’s, Master’s, or PhD in Data Science, Statistics, Computer Science, or a related field

• 3 years of work experience in a related technical field, or 5-7 years relevant applied academic experience

• Proven experience in data analysis, modeling, and performance evaluation

• Strong proficiency in Python, and specifically data analysis libraries (Pandas, Numpy), Data Visualization (Python matplotlib Plots, Excel Plots / BI tools), and SQL

• Ability to interpret and communicate complex data insights to both technical and business audiences

• Exceptional problem-solving and analytical skills with a focus on actionable results

• Interest in developing deep domain expertise for model risk analysis and model governance work

• Ability to thrive in a fast paced environment characterized by the need to solve extremely varied, high impact, open ended problems

• Proven experience in assessing the quality, stability, performance and behavior of production grade ML models, ideally from the perspective of model governance, fair lending or economic risk is highly preferred

• Familiarity with fraud detection preferred

• Experience with GitHub

• Candidates must be legally authorized to work in the United States and must live in the United States

Technologies:

• Python, Pandas, Numpy, matplotlib, BI tools, SQL

Salary:

• $140,000/year - $180,000/year + equity + benefits

• Employer paid group health insurance for you and your dependents

• 401(k) plan with employer match (or equivalent for non US-based roles)

• Flexible paid time off

• Regular company-wide in-person events

• Home office stipend, and more!

• Follow Through

• Deep Understanding

• Whatever It Takes

• Do Something Smart