As a Senior Applied ML Scientist, you'll play a central role in designing and deploying advanced machine learning systems that detect fraud and assess financial risk. You'll guide models from initial concept through deployment and monitoring, making key decisions at every stage—from data sourcing and feature design to training, validation, and real-time implementation.
What You'll Do
- Own the full modeling lifecycle, including defining data needs, engineering features, training models, running experiments, and ensuring reliable performance in production.
- Develop core algorithms that power identity verification and risk assessment products, shaping the future of financial trust and security.
- Investigate emerging fraud patterns and translate findings into new product capabilities or model improvements.
- Collaborate with engineering, data, and operations teams to ensure data quality, access, and scalability.
- Produce clear analyses that guide strategic decisions across product, marketing, sales, and risk operations.
- Write robust, production-grade code that supports real-time decisioning at scale.
Requirements
- PhD with 4+ years or Master’s with 6+ years of hands-on experience in machine learning, statistics, or a related technical field.
- Demonstrated success solving high-stakes business problems using data science and ML.
- Strong command of end-to-end model development: defining objectives, aligning stakeholders, building solutions, and delivering results in production or strategic documentation.
- Practical expertise in statistical modeling and ML techniques, with the ability to quickly prototype and refine approaches.
- Experience writing and testing production code in Python or similar languages.
- Ability to communicate technical outcomes clearly to leadership and cross-functional partners.
- Detail-oriented mindset with a track record of making decisions that significantly impact business outcomes.
- Willingness to dive deep into fraud and identity domains, even without prior experience.
- Must be legally authorized to work in the United States and reside within the country.
Preferred Qualifications
- Familiarity with identity verification, fintech, or adjacent sectors.
- Background working in startups or high-growth environments.
- Thrives when tackling diverse, open-ended challenges with significant business implications.
Technical Environment
Python 3, PostgreSQL, and AWS services including EC2, S3, RDS, and Redshift form the backbone of our infrastructure. You’ll work directly with these tools to build scalable, reliable systems.
Work Mode
This role supports flexible work arrangements, including remote, hybrid, and in-office options. Key locations include Austin, San Francisco, New York City, Seattle, Los Angeles, Chicago, Gurugram, and Bengaluru. The engineering team in India primarily operates from the Gurugram office.
Benefits
- Employer-paid health insurance for employees and dependents
- 401(k) plan with company match
- Flexible paid time off
- Home office stipend
- Regular in-person company gatherings
