• Lead the design, development, and deployment of advanced ML models for complex use cases. • Partner with data engineers and product teams to ensure models are scalable and reliable. • Continuously optimize algorithms for performance, accuracy, and efficiency. • Own end-to-end model deployment processes and manage MLOps best practices. • Act as a custodian of organizational data and drive adoption of analytics and data-driven decision-making. • Mentor junior data scientists and analysts.

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. We have also been named a 2026 FICO Industry Vanguard Decision Award Winner. 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. Role:As a Senior Data Scientist at SentiLink, you will build our core products: models that identify fraudsters and also advance our growing suite of products in financial risk. As an experienced researcher you will be relied upon to be technically capable and the definitive owner of your respective domain. You will often work on projects with high visibility and impact that require deep domain understanding, critical thinking and strong technical abilities. You will work with teams across the company to research new types of fraud, develop new products, and provide analysis to drive sales and marketing. This is a full-stack data science role, involving model development, analysis, and writing production code. You should be interested in having end-to-end ownership and a fast-moving environment where deep domain understanding drives development and unusual insights drive our competitive advantage rather than optimization of new machine learning methodologies. We have open roles on multiple teams including: - Emerging Products - focuses on 0-to-1 development of new offerings brought to market - Application Fraud - analyzes the foundational elements of consumer financial applications to detect all forms of fraud - Identity - resolves identities across massive, often conflicting data sources (both digital and physical) and generates risk models from limited information Technologies: Python 3, PostgreSQL, and AWS infrastructure (EC2, S3, RDS, Redshift, etc.) Responsibilities: - Develop and maintain SentiLink’s fraud detection models through the full model development lifespan: from data acquisition decisions through featurization, focusing labeling resources, model training, experimentation, productionalization, and monitoring. - Build foundational modeling to drive SentiLink’s expanding suite of Fraud and Financial Risk products. - Research new types of fraud and develop new SentiLink products around identity verification. - Achieve success by researching / developing through iteration, integration of new data sources and inventive feature engineering. - Write production-ready code that can be relied on for real-time decision making by our partners. - Design, perform, and present analyses that will inform data acquisition, product development, risk operations priorities, marketing, and sales efforts. - Work with engineering, risk operations, and data acquisitions to access necessary data, maintain data quality, and support data access Requirements: - 4+ years relevant work experience & relevant PhD or 6+ years & relevant Masters - Proven track record of solving complex / high profile business problems with DS / ML solutions - Experience in communicating outcomes / progress to senior management / stakeholders - Very strong in “end to end” DS development: Planning, fleshing out success criteria / metrics, getting buy-in, developing the solution, delivering the solution (prod / deck / strategy doc / etc) - Strong practical ML / Stats knowledge, i.e. can easily employ the suite of standard ML / stats tools to quickly scope out solutions, and double down where needed. Experience with SOTA ML solutions is a plus - Interest in developing deep domain expertise for product-focused work: a background in fraud is not required, but willingness to learn is - Experience writing production code and tests - Detail oriented and thoughtful - someone we can rely on to make business-changing decisions - Bonus for familiarity with: identity solutions, fintech, or adjacent industries - Experience working at a startup strongly preferred - Thrive in a fast paced environment characterized by the need to solve extremely varied, high impact, open ended problems. - Candidates must be legally authorized to work in the United States and must live in the United States Salary Range: - $200,000/year - $240,000/year + equity + benefits Perks: - 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! Corporate Values: - Follow Through - Deep Understanding - Whatever It Takes - Do Something Smart

• Lead the collection, evaluation, and management of market data across multiple asset classes, including futures, futures options, equities, equity/index options, foreign exchange (FX), market statistics, spreads, and strategy spreads • Direct data exploration, statistical analysis, modeling, and trend analysis efforts to identify insights, anomalies, and business opportunities • Oversee the analysis of structured and unstructured market data and ensure methodologies remain accurate and effective • Establish and maintain procedures that ensure data accuracy, integrity, completeness, and consistency • Develop and oversee quality assurance processes that validate data inputs, mappings, and outputs • Manage proprietary cross-referencing and classification of market assets • Lead efforts to investigate and resolve market data issues, discrepancies, and reported errors • Guide the development of dashboards, reports, documentation, and stakeholder communications that support analytical findings • Establish standards and best practices for market data capture, structuring, governance, and usage • Partner with Development, Operations, Risk, and business stakeholders to improve data quality, workflows, and operational processes • Identify and prioritize enhancements to data models, analytics tools, reporting frameworks, and data management capabilities • Lead, mentor, and develop team members while evaluating performance, addressing skill gaps, and supporting career growth

• You are the ideal candidate if you have experience managing large scale, complex programs and projects related to business process and system transformation, ideally ERP implementation using SAP’s S4 HANA solution. • The Functional Data Lead Analyst will coordinate conversion activities, translate and document conversion requirements and detailed plans. • They will drive execution tasks with various team members and stakeholders, track progress, and escalate issues. • The Functional Data Lead Analyst will be expected to follow project management processes and best practices to ensure all tasks, activities, and resources are aligned to meet the overall program and organizational goals. • Work cross functional to complete Build Phase, support system configuration design, testing, migration and hyper-care activities • Completion of conversion functional specification documents, data mapping, cross reference documents and data model documents across multiple deployments • Drive conversion progress, including task completion, milestone achievement to adhere to overall timeline. • Lead meetings with cross functional thread leads • Understanding team member workload, potential resource constraints, and ensure optimal resource utilization throughout the conversion process. • Proactive risk management: identify, assess, mitigate, and monitor potential risks with real-time alerts for critical issues. • Monitor and track conversion and deviation issue resolution. • Communicate expectations and instill accountability in team members • Resolve conflicts, promote work sharing, and motivate teams toward common goals. • Manage multiple conversion activities, tasks and resources through effective organization prioritization, and time management practices to meet program objectives. • Additional responsibilities include documentation, profiling analytics, reporting, internal stakeholder communication, and identifying areas for improvement to enhance quality and efficiency of cutover activities.