Applied Science Intern

Carrerlift; New York (NY); On-site; USD 150,000 - 170,000; Full time

Benefits offered by this job

Housing stipend

Apple MacBook provided

Catered weekday lunches (NYC office)

Weekly coffee stipend

Job summary

Ramp’s Applied Science internship offers a hands-on role on an integrated team, owning an ML project end-to-end. You’ll work with engineers, product managers and business stakeholders to turn complex requirements into scalable ML solutions that ship production code and create measurable value for Ramp and customers.

You will explore data, engineer features, train models, benchmark, deploy and monitor, and apply AI/LLMs to expand customer-facing capabilities while collaborating with product teams.

Qualifications

• Pursuing degree with expected graduation Dec 2027–Dec 2029.
• Strong foundations in ML math, statistics, probability and optimization.
• Interest or experience applying AI/LLMs to practical problems.
• Proficient in Python with pandas, scikit-learn, NumPy and PyTorch.
• Knowledge of SQL and warehouses like Snowflake, BigQuery, Redshift or ClickHouse.
• Experience preparing datasets and building ML models.
• Strong communication to explain complex ideas and tell data-driven narratives.
• Comfortable with ambiguity and shipping solutions.

Responsibilities

• Manage the full ML lifecycle from data exploration to deployment and monitoring.
• Apply modern LLMs to create customer-facing capabilities.
• Select techniques such as deep learning, gradient boosting, and causal inference.
• Measure results with A/B testing and other experiments.
• Partner with product/business teams to translate model outputs into strategy and user features.

Skills

Python

SQL

Pandas

scikit-learn

NumPy

PyTorch

Communication

Education

Pursuing B.S./M.S./Ph.D. in Data Science, CS, Math, Physics, Economics, Statistics

Tools

Snowflake

BigQuery

Redshift

ClickHouse

Airflow

Dagster

Prefect

Metaflow

Git

Job description

Batch: Dec 2027 - 2029. About the role:

• Join Ramp's Applied Science team, which develops quantitative models and tools for areas including business underwriting, fraud prevention, spend management, credit, growth and core product experiences.
• Interns operate as integrated team members, owning a project end to end while working with engineers, product managers and business stakeholders.
• The work involves turning complex business requirements into scalable machine-learning solutions, shipping production code and creating measurable value for Ramp and its customers.

What you'll work on:

• Manage the full ML lifecycle, covering data exploration, feature engineering, model training, benchmarking, deployment and monitoring.
• Apply modern LLMs to new problems and use them to create additional customer-facing capabilities.
• Select techniques based on the problem, including deep learning, gradient boosting and causal inference.
• Measure results through A/B testing and other statistical experimentation methods.
• Partner with product and business teams to turn model outputs and analytical insights into strategy and user-facing functionality.

What we're looking for:

• Applicants must currently be pursuing a B.S., M.S. or Ph.D. in Data Science, Computer Science, Math, Physics, Economics, Statistics or another quantitative discipline, with expected graduation between Dec 2027 - 2029; graduate-level study is preferred but not mandatory.
• Strong foundations in machine learning mathematics, statistics, probability and optimization are required.
• Candidates should have strong interest or experience in applying advanced AI, including LLMs and agents, to practical problems.
• Python proficiency is expected, including familiarity with tools such as pandas, scikit-learn, NumPy and PyTorch.
• Applicants should know SQL and have experience manipulating data in modern warehouses such as Snowflake, BigQuery, Redshift or ClickHouse.
• Practical experience preparing datasets and building and evaluating ML models is required.
• Strong communication skills are important, including explaining complex ideas to technical and non-technical audiences and using data to construct a clear narrative.
• Candidates should be comfortable with ambiguity, move quickly toward shipping solutions and iterate after launch.

Nice to have:

• Relevant AI/ML publications, projects or previous experience are beneficial.
• Knowledge of production-oriented ML engineering practices such as Git, testing and maintainable code is useful.
• Experience with orchestration tools including Airflow, Dagster, Prefect or Metaflow is a plus.

Compensation and benefits:

• The internship pays a monthly rate of $12,500 USD plus a housing stipend and provides an Apple MacBook, catered weekday lunches in the NYC office and a weekly coffee stipend.
• Benefits listed for full-time Ramp employees globally include flexible PTO, centralized home-office equipment ordering, a health and wellness stipend, intra-office travel budget and weekly coffee support.
• U.S. full-time benefits listed include 100% employee medical, dental and vision coverage with partial dependent coverage, One Medical membership, a matched 401(k), fertility HRA up to $10,000 annually, paid parental leave, pet insurance, office food and drinks, and relocation expense coverage to NYC or SF when needed; Canada benefits include Sun Life health coverage, life/AD&D/disability insurance, fertility drug coverage up to $4,000 lifetime, matched RRSP and DPSP retirement plans, parental leave, an Employee Assistance Program and Lumino Health virtual care; UK benefits include Freedom Elite private medical insurance, eMed x Livi virtual GP and home care, a Penfold workplace pension with salary sacrifice, and parental leave.

About Ramp and other information:

• Ramp builds finance infrastructure embedded in business spending flows and says it automates more than $200B in annualized spend across 70,000+ companies through functions such as payment authorization, risk detection, spend categorization and book closing; Ramp states that its median customer saves 5% and grows revenue 16% in the first year.
• The company emphasizes high agency, urgency, end-to-end ownership and demonstrated building ability over traditional pedigree.
• Qualified applicants with arrest or conviction records will be considered in accordance with the San Francisco Fair Chance Ordinance.
• Ramp warns candidates that legitimate recruiting communication comes only from official @Ramp.com addresses and that it will not request payment or sensitive personal information during hiring.