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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in building and deploying machine learning models, particularly in fraud detection and identity threat systems. Proficient in leveraging statistical techniques and data architectures to enhance decision-making and mitigate fraud-related risks.
Highest-signal resume keywords
Machine Learning Model DevelopmentPython Programming (NumPy, Pandas, Scikit-Learn, PyTorch)SQL Proficiency (Snowflake, Postgres)Fraud Detection Systems KnowledgeData Architecture Design
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Machine LearningStatistical AnalysisData AnalysisModel DeploymentBackend Engineering
Soft Skills
AdaptabilityCollaborationProblem-Solving
Tools & Technologies
SnowflakeHexDbtRisingWaveAgentic AI Tools
Certifications & Qualifications
Bachelor’s Degree in Quantitative FieldPhD in Quantitative Field (Nice-to-Have)
Industry Keywords
Fraud DetectionIdentity TheftHigh-Growth StartupModern Data StackML Engineering Development Cycles
Tech Stack
Tools & technologiesNumpyPandasPostgresPythonPyTorchScikit-LearnSQL
About the role
Key responsibilities & impact- Lead the future of fraud machine learning at Ramp
- Build core machine learning models
- Design data architectures and set strategic roadmaps to mitigate fraud-related threats while minimizing friction for legitimate users
- Partner with product and engineering counterparts on model design, implementation, execution, and analysis
- Apply statistical and machine learning techniques to large datasets to discover fraud, platform abuse, and identity-theft patterns
- Prototype and productionize machine learning models and rules-based fraud protection systems
- Partner with Fraud Engineering and Data Platform teams to augment and leverage first- and third-party data sources
- Influence machine learning team processes, tools, and systems to enable scalable decision-making
Requirements
What you’ll need- Bachelor’s degree or above in Math, Economics, Physics, Computer Science, or other quantitative fields
- Minimum of 5 years of industry experience as a Machine Learning Engineer, Applied Scientist, or Data Scientist
- Strong Python experience (NumPy, pandas, scikit-learn, PyTorch, etc.) across ML techniques and backend engineering
- Prior experience deploying machine learning models to production and contributing meaningfully to backend systems
- Strong knowledge of SQL (Snowflake, Postgres, etc.)
- Fluency with agentic AI tools for software development and data analysis
- Ability to thrive in a fast-paced, constantly improving startup environment
- PhD in a quantitative field (nice-to-have)
- Context on fraud and/or identity threat detection systems (nice-to-have)
- Experience at a high-growth startup (nice-to-have)
- Experience with the modern data stack (Snowflake, Hex, dbt, RisingWave, etc.) (nice-to-have)
- Strong perspective on data science and ML engineering development cycles (nice-to-have)
- Experience developing LLM-backed systems or tools (nice-to-have)
Benefits
Comp & perks- Flexible PTO
- Centralized home-office equipment ordering
- Health and wellness stipend
- Budget for intra-office travel
- Weekly coffee stipend
- 100% medical, dental & vision insurance coverage for you, with partial coverage for dependents
- One Medical annual membership
- 401(k), including employer match
- Fertility HRA (up to $10,000 per year)
- Parental leave: up to 16 weeks (birthing + bonding) or 8 weeks (bonding only) at 100% pay
- Pet insurance
- In-office perks: lunch, snacks, drinks, and more
- Relocation expense coverage to NYC or SF (if needed)
- Group medical, dental, and vision coverage through Sun Life
- Life, AD&D, and disability coverage
- Fertility drug coverage (up to $4,000 lifetime)
- Group Retirement Plan with employer match (RRSP + DPSP)
- Employee Assistance Program and virtual care through Lumino Health
- Private medical insurance through Freedom Elite
- Virtual GP and at-home care via eMed x Livi
- Workplace pension through Penfold, with salary sacrifice option