At a glance
- Location
- Menlo Park
- Salary
- USD 44-44
About the role
- As a Data Scientist Intern on the Brokerage Data Science team, you'll be part of a high-impact, multi-functional group working closely with partners across product, engineering, user research, design, marketing, finance, and operations.
- Unlock the power of data to shape the future of our brokerage business and deliver outstanding value to our customers.
- Accelerate product growth through world-class experimentation, analysis, and data-informed strategy.
Responsibilities
- Partner directly with a current team member on a specific product line (e.g., Agentic Trading, Prediction Markets, Portfolio Margin, Trading Products, Trading Tools, Robinhood Social, Legend, etc).
- Perform deep-dive analyses to identify product growth opportunities and drive improvements in core business metrics.
- Design, plan, implement, and analyze A/B experiments, and conduct causal inference analysis to evaluate product changes.
- Gain expertise in predictive modeling, uplift modeling, causal inference, and experimentation design.
- Define and maintain key product performance metrics; build scalable dashboards to monitor these metrics and advise decision-making.
- Build compelling data visualizations and narratives to effectively communicate insights and recommendations to multi-functional partners, collaborators, and senior leadership.
- Lead and implement large-scale analytics projects to uncover user insights, inform product strategy, and deliver measurable business impact.
- Partner closely with Product, Engineering, Operations, and other multi-functional teams to integrate data-driven decision-making into product and business processes.
- Assist with established methods, standard approaches, and promote a data-informed culture within the organization.
Requirements
- Currently enrolled in a full-time, graduate degree program with an expected graduation date in Winter 2027 or Spring 2028.
- Pursuing a graduate degree in a quantitative field such as mathematics, statistics, engineering or natural science.
- Proven expertise in data science, with a strong background in statistical analysis and machine learning.
- Outstanding problem-solving skills and the ability to think critically and creatively.
- Strong programming skills in Python & SQL, or other relevant languages.
- Experience with data visualization tools and techniques.
- Ability to successfully implement projects and compete in a fast-paced environment.
Preferred qualifications
- Previous experience working in financial technology is preferred.
Workplace
- In-person attendance expected at least 3 days per week in the Menlo Park office.
Skills
- Python
- SQL
- Machine Learning
- Statistical Analysis
- Data Visualization
- Experimentation Design
- Predictive Modeling
- Causal Inference
