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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in machine learning model development, including data exploration, feature engineering, and deployment. Proficient in Python and familiar with data science libraries, with a strong understanding of statistical methods and the ability to communicate complex concepts effectively.
Highest-signal resume keywords
Machine Learning Model DevelopmentPython ProficiencyLarge Language Models IntegrationStatistical AnalysisData Wrangling
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 LearningDeep LearningGradient BoostingCausal InferenceA/B TestingData ExplorationFeature EngineeringModel DeploymentStatistical MethodsOptimization
Soft Skills
CommunicationProblem-SolvingAdaptability
Tools & Technologies
PandasScikit-LearnNumPyPyTorchSQLSnowflakeBigQueryRedshiftClickHouseGit
Industry Keywords
Data ScienceQuantitative AnalysisAI/ML PublicationsSoftware Engineering Best PracticesData Warehouse
Tech Stack
Tools & technologiesAirflowAmazon RedshiftBigQueryNumpyPandasPythonPyTorchScikit-LearnSQL
About the role
Key responsibilities & impact- Build models and tools solving critical problems in underwriting, fraud, spend management, credit, growth, and core product areas
- Own applied ML projects from start to finish as an integrated team member
- Translate complex business needs into scalable machine-learning-driven solutions
- Own the model lifecycle from data exploration and feature engineering through training, benchmarking, deployment, and monitoring
- Leverage Large Language Models to solve novel problems and create product capabilities
- Apply deep learning, gradient boosting, causal inference, and other appropriate techniques
- Quantify impact through A/B tests and other statistical methods
- Partner with engineers, product managers, and business stakeholders
- Translate models and insights into actionable strategy and user-facing features
- Ship code and create value for Ramp and its customers
Requirements
What you’ll need- Currently pursuing a B.S., M.S. or Ph.D. in Data Science, Computer Science, Math, Physics, Economics, Statistics, Engineering, or another quantitative field
- Expected graduation date between Dec 2027 and 2029
- Strong understanding of mathematical foundations of machine learning, statistics, probability, and optimization
- Strong interest or experience integrating cutting-edge LLMs and agents into applied solutions
- Python proficiency and familiarity with pandas, scikit-learn, NumPy, PyTorch, and similar data science libraries
- SQL knowledge and experience wrangling data in a modern data warehouse such as Snowflake, BigQuery, Redshift, or ClickHouse
- Track record of curating datasets and building/evaluating ML models
- Ability to clearly explain complex concepts to technical and non-technical audiences and use data to build a compelling narrative
- Comfort with ambiguity and desire to ship solutions quickly and iterate
- Relevant AI/ML publications, projects, or previous experience are nice to have
- Knowledge of ML software-engineering best practices, Git, testing, and maintainable code is a nice to have
- Experience with Airflow, Dagster, Prefect, or Metaflow is a nice to have
- Willingness to relocate to the greater NYC area for the duration of the internship
- Must answer whether employment visa sponsorship will be required
Benefits
Comp & perks- $12,500 USD monthly internship rate
- Housing stipend
- Apple MacBook
- Catered lunches in NYC office Monday-Friday
- Weekly coffee stipend
- Flexible PTO
- Centralized home-office equipment ordering
- Health and wellness stipend
- Budget for intra-office travel
- 100% medical, dental & vision insurance coverage for you, with partial coverage for dependents (United States)
- One Medical annual membership
- 401(k), including employer match on contributions made while employed by Ramp
- 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 (Canada)
- Life, AD&D, and disability coverage (Canada)
- Fertility drug coverage (up to $4,000 lifetime) (Canada)
- Group Retirement Plan with employer match (RRSP + DPSP) (Canada)
- Employee Assistance Program and virtual care through Lumino Health (Canada)
- Private medical insurance through Freedom Elite (United Kingdom)
- Virtual GP and at-home care via eMed x Livi (United Kingdom)
- Workplace pension through Penfold, with salary sacrifice option (United Kingdom)