Data Science & Machine Learning Intern
RockWallet is a self-custodial, multi-currency cryptocurrency wallet for buying, selling, swapping, sending, receiving, and holding digital assets. It targets crypto-curious and beginner users, while also offering an OTC trading desk for institutional and high-net-worth clients.
About RockWallet
RockWallet provides a secure, user-friendly mobile cryptocurrency wallet designed to make digital asset management accessible. Its app supports self-custody and guides users through buying, selling, swapping, sending, receiving, and storing a curated range of digital assets, with account recovery and customer support. RockWallet is registered with FinCEN as a Money Services Business and offers U.S. users services including ACH purchases where available. It also operates a premium OTC desk for institutional and high-net-worth clients seeking larger digital-asset trades, liquidity, competitive pricing, and dedicated support.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
You will support the development of analytics and predictive models using real customer, product, and operational data. You will help model customer behavior, detect anomalies, forecast key metrics, prepare data, engineer features, evaluate models, analyze large datasets, build dashboards and reports, collaborate with business teams, document results, and experiment with data science techniques under guidance.
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, including pandas, numpy, and scikit-learn
- Working knowledge of SQL for querying and aggregating data
- Understanding of statistical concepts, regression, classification, and model evaluation
- Familiarity with time-series data, forecasting, or anomaly detection concepts
- Comfort 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
Responsibilities
- Assist in developing and evaluating predictive models to understand customer behavior
- Support anomaly detection analyses to identify unusual patterns in product, marketing, or financial data
- Help build forecasting models for 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 define business questions and success metrics
- Document analyses, assumptions, and results for technical and non-technical audiences
- Explore and experiment with new data science techniques, tools, and models under guidance