Data Science & Machine Learning Intern

Data Science & Machine Learning Intern

About RockWallet

Rock Solid. Rock Confident.

RockWallet is a financial technology company made up of people who think differently about how digital assets can be managed, accessed, and used.

At RockWallet, our vision is for anyone to be able to access and thrive in the digital economy. It’s our mission to help our customers make the most of these opportunities by building products that empower people to navigate digital asset usage easily, securely, and with confidence. Our self-custodial, multicurrency wallet puts you in charge of your digital assets. RockWallet’s app makes it quick and easy to buy, use, store, and swap top cryptocurrencies, all in one place, on your mobile phone. We are a customer-focused company obsessed with providing the best customer experience and customer support. RockWallet is registered with FinCEN as a Money Service Business. Find out more here at www.rockwallet.com.

Want to join us?  We’re expanding our team globally, looking for the right people to help us grow.

Role Overview

We’re looking for a Data Science & Machine Learning Intern to join the RW Data Team and support the development of analytics and predictive models that drive real business decisions. This role offers hands-on exposure to applied data science in a production environment, working with real customer, product, and operational data.

You will contribute to projects such as customer behavior modeling, anomaly detection, and forecasting key metrics, while learning how data science solutions are built, validated, and deployed in practice.

This internship bridges theory and application, combining statistical thinking, experimentation, and practical machine learning to generate actionable insights.

Key Responsibilities

• Assist in developing and evaluating predictive models to understand customer behavior (e.g., engagement, churn, conversion).
• Support anomaly detection analyses to identify unusual patterns in product, marketing, or financial data.
• Help build forecasting models for key metrics such as transaction volume, revenue, and customer activity.
• Work with senior data scientists and data engineers to prepare data, engineer features, and test models.
• Analyze large datasets from multiple sources to identify trends and opportunities for optimization.
• Contribute to dashboards, reports, and internal tools that surface insights to stakeholders.
• Collaborate with product, marketing, and operations teams to understand business questions and define success metrics.
• Document analyses, assumptions, and results clearly for both technical and non-technical audiences.
• Explore and experiment with new data science techniques, tools, and models under guidance.

Qualifications & Requirements

• Currently pursuing or recently completed a degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, or a related quantitative field.
• Strong foundation in Python (pandas, numpy, scikit-learn; PySpark is a plus).
• Working knowledge of SQL for querying and aggregating data.
• Understanding of basic statistical concepts, regression, classification, and model evaluation.
• Familiarity with time-series data, forecasting, or anomaly detection concepts (academic or project-based).
• Comfortable working with messy, real-world datasets and learning data cleaning techniques.
• Strong analytical thinking and curiosity about how data translates into business impact.
• Good communication skills and willingness to ask questions and learn.

Nice to Have

• Coursework or projects involving machine learning, forecasting, or anomaly detection.
• Exposure to AWS or cloud data tools (S3, Redshift, Glue, SageMaker) through school or projects.
• Experience with data visualization tools (QuickSight, Power BI, Tableau, or similar).
• Interest in fintech, transactional data, fraud analytics, or customer segmentation.
• Familiarity with notebooks, Git, or basic ML pipelines.
• Exposure to NLP or LLM-based analytics (coursework or side projects).

What You’ll Gain

• Hands-on experience working with real production-scale data.
• Exposure to end-to-end data science workflows — from raw data to insights and models.
• Opportunity to contribute to projects that directly impact product and business decisions.
• A strong foundation for future roles in Data Science, Machine Learning, or Analytics.

HOW TO APPLY: Please submit your resume in our preferred file – .PDF not in .DOC. Thank you.

We thank all interested applicants; however, only those under consideration will be contacted.

RockWallet, LLC is an Equal Employment Opportunity/ Veterans/Disabled/LGBT and Affirmative Action employer. We are committed to diversity and building a team that represents a variety of backgrounds, perspectives, and skills. We do not discriminate and all decisions we make are made on the basis of qualifications, merit, and business need. Our goal is to be one global diverse team that is representative of our customers, in an inclusive environment where we can continue to innovate and grow together.

This job posting may involve the use of artificial intelligence (AI) — such as automated resume screening or candidate assessment — at one or more stages of the recruitment process. If AI tools are used, all decisions are overseen by a human reviewer.