Data Science & Machine Learning Intern
Summary
Build and evaluate predictive models, detect anomalies, and forecast metrics using Python, SQL, and data science libraries to support fintech product decisions.
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.
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
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