Solutions Analytics Data Scientist
SentiLinkUnited StatesPosted 26 March 2026
Tech Stack
Job Description
Solutions Analytics Data Scientist
SentiLink https://www.sentilink.com/ 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 https://www.forbes.com/companies/sentilink/?list=fintech50 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 https://resources.sentilink.com/blog/sentilink-makes-history-as-first-ecbsv-provider and testified before the United States House of Representatives https://resources.sentilink.com/media/sentilinks-statement-before-the-house-financial-services-committee 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.
ABOUT THE OPPORTUNITY:
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., Tableau, matplotlib).
- 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 domai ... (truncated, view full listing at source)
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