About the Role:We are seeking an experienced
Data Scientist to own the identity verification and fraud monitoring systems at the heart of Jaris's merchant onboarding and embedded finance products. You'll work within a modern Databricks-native ML stack building real-time detection systems, modeling identity and transaction data for a diverse set of Small and Medium-sized Businesses, and continually refining prevention strategies as fraud patterns evolve.
You will have the opportunity to work on cutting-edge projects at the intersection of data science, economics, and finance in a collaborative and dynamic work environment with ample room for professional growth and development.
If you are passionate about leveraging data to drive impactful decisions and thrive in a fast-paced environment, we encourage you to apply for this exciting opportunity!
Responsibilities:- Identify emerging fraud patterns (application fraud, synthetic identity, chargeback fraud, merchant-level risk) from a diverse dataset of SMBs spanning multiple industries.
- Build predictive models and rules-based systems for fraud detection, identity verification, and BSA/AML compliance across Jaris' embedded financial products.
- Partner cross-functionally with Compliance, Risk Operations, and Engineering to translate risk policies into reliable, production-grade systems.
- Integrate signals from first and third-party data sources (KYB/KYC providers, transaction history, behavioral features) into production feature pipelines.
- Develop metrics and monitoring to track model health and performance.
- Apply LLMs and generative AI techniques to entity enrichment, document analysis, and investigator tooling where appropriate.
Qualifications:- 2 - 4 years of experience in a data science or machine learning role, preferably with a focus on fraud detection, identity risk, or financial risk modeling.
- Bachelor's degree in a quantitative field, such as Statistics, Computer Science, Mathematics, Finance, or similar.
- Proficient in Python and SQL, including common data science frameworks such as scikit-learn, XGBoost/LightGBM, and PySpark.
- Strong understanding of fraud-specific ML challenges such as class imbalance, adversarial adaptation, and precision-recall tradeoffs.
- Professional experience maintaining models in production, including drift detection and model alerting.
- Excellent communication skills with the ability to convey complex outcomes to non-technical stakeholders.
- In-office in Burlingame, CA at least 3 days per week.
Nice to have:- An advanced degree (M.S. or Ph.D) is highly preferred but not required given a suitable combination of education and experience.
- Knowledge of model governance, explainability requirements, or regulatory contexts relevant to lending and banking.
- Familiarity with streaming or event-driven data pipelines is a plus.
Applicants located in the San Francisco Bay Area can expect an annual base compensation in the range of $95,000 to $140,000 USD. This salary range may be inclusive of several career levels at Jaris and will be narrowed during the interview process based on a number of factors, including the candidate's experience, qualifications, and location.
Additional benefits include: - Company equity
- 401(k) plan with a corporate match
- Employee Assistance Program through Optum
- Commuter benefits
- Medical, dental, and vision benefits (PPO/HMO/HDHP options)
- Health & Financial Wellness through a Partnership with Calm, Insperity & MSA (My Secure Advantage)
- Caregiver Support Program
- Flexible PTO
