Solutions Analytics Data Scientist

SentiLink provides innovative identity and risk solutions, empowering institutions and individuals to transact confidently with one another. By building the future of identity verification in the United States and reinventing the currently clunky, ineffective, and expensive process, we believe strongly that the future will be 10x better. We’ve had tremendous traction and are growing extremely quickly. Already our real-time APIs have helped verify hundreds of millions of identities, beginning with financial services. In 2021, we raised a $70M Series B round, led by Craft Ventures to rapidly scale our best in class products. We’ve earned coverage and awards from TechCrunch, CNBC, Bloomberg, Forbes, Business Insider, PYMNTS, American Banker, LendIt, and have landed on the Forbes Fintech 50 in 2023 and 2024. Last but not least, we’ve even been a part of history -- we were the first company to go live with the eCBSV and testified before the United States House of Representatives.

Role:

As a Solutions Analytics Data Scientist, you will play a crucial role in enabling current and prospective partners to implement and optimize SentiLink products. You will conduct data evaluations that demonstrate how SentiLink’s solutions add measurable value to partners' businesses. This includes analyzing partner data, interpreting key data science metrics, and illustrating product performance. For existing partners, you will provide ongoing performance assessments, support product evaluations, and deliver custom analyses to help partners understand fraud patterns and their impact on consumers and business operations.

Technologies: Python 3, PostgreSQL, and AWS infrastructure (EC2, S3, RDS, Redshift, etc.)

This is a remote, US-based role.

Responsibilities:

• Conduct comprehensive data evaluations for prospective partners, demonstrating SentiLink's product value through clear data science metrics.
• Analyze performance data from current partners to ensure optimal product use and provide actionable recommendations.
• Collaborate with cross-functional teams, including Product, Data Science, and Engineering, to enhance product performance and address partner-specific needs.
• Deliver ad hoc analyses and reports that provide deep insights into fraud trends, consumer behavior, and partner-specific challenges.
• Communicate complex data findings effectively through visualizations, reports, and presentations tailored to both technical and non-technical stakeholders

Requirements:

• Bachelor’s or Master’s degree in Data Science, Statistics, Computer Science, or a related field.
• Proven experience in data analysis, modeling, and performance evaluation.
• Strong proficiency in data tools and languages such as Python, R, SQL, and data visualization libraries (e.g., …