Applied ML Scientist

Ovii's Interpretation of the Role

SentiLink seeks an Applied ML Scientist to design, build, and ship fraud‑detection and financial‑risk models. The role offers end‑to‑end ownership of the ML lifecycle, from research through production, in a fast‑moving, remote‑first environment.

Role Snapshot

• Full‑stack data science
• End‑to‑end ML model lifecycle
• Fraud detection focus
• Remote (U.S.) with office preference
• Python & AWS stack
• Cross‑functional collaboration

Must-Have Requirements

• Python
• Machine Learning
• Statistics
• Data Science
• Clean code
• Strong communication
• machine learning
• statistical modeling
• Python programming
• Bachelor's in Statistics, Computer Science, Physics, Mathematics, or related field
• Master's in Statistics, Computer Science, Physics, Mathematics, or related field
• PhD in Statistics, Computer Science, Physics, Mathematics, or related field
• must be legally authorized to work in the United States
• must live in the United States

Nice-to-Have Signals

• Interest in fraud and identity systems

Work Setup

• Location: United States
• Work mode: REMOTE
• Remote scope: COUNTRY_RESTRICTED
• Remote countries: United States
• Employment type: Full-Time

Eligibility Gates

• Work authorization: must be legally authorized to work in United States
• Visa sponsorship: no

Not Specified in JD

• Travel requirement
• Security clearance

What You'll Likely Work On

• Develop and maintain fraud‑detection models across the full ML lifecycle, including data acquisition, labeling, training, experimentation, deployment, and monitoring
• Create foundational models that power SentiLink’s expanding suite of financial‑risk products
• Research emerging fraud patterns and translate findings into new identity‑verification offerings
• Engineer inventive feature pipelines and integrate novel data sources to improve model performance
• Write production‑ready code that powers real‑time decision making for partners
• Design, execute, and present analyses that guide product development, risk operations, marketing, and sales strategies
• Partner with engineering, risk operations, and data acquisition teams to ensure data quality and accessibility

Good Fit If You Have

• Interest in fraud, identity, and financial‑risk systems
• Thrives in a fast‑paced, high‑impact problem‑solving environment
• Detail‑oriented with strong curiosity about real‑world data