Applied Scientist, PhD New Grad

Ovii's Interpretation of the Role

SentiLink seeks an early‑career Applied Scientist to design, build, and ship machine‑learning models that detect fraud and verify identity. The role offers full‑stack data‑science ownership, from research through production, in a fast‑moving fintech environment. Remote work is allowed within the United States, with a preference for Austin, San Francisco, or New York.

Role Snapshot

• Full‑stack data science
• ML model development & deployment
• Fraud detection focus
• End‑to‑end ownership
• Remote (U.S.) with office preference
• New PhD graduate / early‑career

Must-Have Requirements

• Python
• Machine Learning
• Statistics
• Feature Engineering
• Model Productionization
• PostgreSQL
• AWS
• Technical Communication
• machine learning
• statistics
• applied data science
• Bachelor’s, Master’s, or PhD in Statistics, Computer Science, Physics, Mathematics, or related quantitative field
• must be legally authorized to work in the United States
• must live in the United States

Nice-to-Have Signals

• Interest in fraud, identity, and financial risk 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 the United States
• Visa sponsorship: no

Not Specified in JD

• Visa sponsorship
• Travel
• 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 novel feature sets by integrating new data sources and applying inventive feature‑engineering techniques
• Write production‑grade code that powers real‑time decision making for partner integrations
• Design, execute, and present analyses that guide product development, risk‑operations priorities, marketing, and sales strategies
• Collaborate with engineering, risk‑operations, and data‑acquisition teams to secure high‑quality data and ensure smooth data pipelines

Good Fit If You Have

• Strong curiosity about real‑world data problems and fraud domains
• Ability to thrive in a fast‑paced, high‑impact environment
• Excellent written and verbal communication for cross‑functional stakeholders