Data Scientist - Growth

At AoPS, data plays a critical role in how we reach, engage, and retain families. We serve tens of thousands of students worldwide, and our marketing efforts span acquisition channels, campaign performance, lifecycle engagement, brand awareness, and community growth. These campaigns and programs generate rich behavioral and performance data, but that data only creates value when it drives better decisions.

We are hiring a Data Scientist to serve as a core analytical partner to the Marketing and Growth teams. This is a full-stack individual contributor role for someone who can conduct deep analyses, build customer segments, measure attribution, design experiments, and answer ambiguous, high-impact marketing questions. The role exists to uplevel our marketing and growth decision-making and close the gap between analytics and strategy.

You will work closely with our marketing and growth teams to shape marketing strategy, evaluate channel performance, and ensure we are reaching and converting the right audiences with messages that resonate and drive enrollment.

The Data Scientist (Growth) will:

• Act as the primary data partner for the AoPS Marketing and Growth teams, supporting marketing strategy, campaign planning, and performance evaluation


• Proactively identify opportunities, risks, and trends in customer acquisition data, surfacing insights without waiting for explicit requests


• Frame ambiguous marketing and business problems, translating goals into testable hypotheses, success metrics, and analytic plans


• Define, own, and evolve marketing and growth metrics, including funnel metrics, attribution models, customer acquisition costs, lifetime value, and channel efficiency, ensuring alignment across teams


• Design and analyze experiments (e.g., A/B tests, creative tests, channel tests) to measure the impact of marketing campaigns and tactics


• Design analytics data models and lightweight pipelines to support analytics and reporting as needed


• Use SQL and Python to conduct analyses, develop models, and produce reproducible, decision-ready insights


• Apply statistical and machine learning techniques where appropriate, while exercising strong judgment about rigor, speed, and tradeoffs


• Communicate findings clearly, influencing marketing prioritization and budget allocation through data-backed recommendations, reports, and dashboards


• Use best practices for marketing analytics, experimentation, and metric integrity, promoting consistent data quality and measurement standards across the organization


• Completes other tasks and responsibilities, as assigned

The ideal candidate has:

• 2+ years of experience in data science, analytics, or a related quantitative role, within marketing and growth contexts (e.g., acquisition, lifecycle, campaigns), with demonstrated impact on decision making


• Proven ability to operate as a strategic thought partner to marketing teams and leadership, building trust and influence across functions including creative, growth, and business stakeholders


• Strong proficiency in Python for data analysis, statistical modeling, and machine learning (e.g., pandas or polars, scikit-learn, statsmodels)


• Strong SQL and data warehouses (e.g., Redshift, Snowflake, BigQuery) skills. We use Redshift


• Experience using tools and best practices for reproducible research (e.g., version-controlled analysis, environment management, documented workflows)


• Strong foundation in experimentation and causal reasoning, including hypothesis testing, experiment design, and observational analysis


• Experience defining and defending marketing metrics that drive alignment and decision-making


• Excellent communication and the ability to translate complex analysis into clear, actionable guidance


• Comfort owning work end-to-end, from raw data through executive-level recommendations

Nice to Have

• Experience with marketing attribution modeling and multi-touch attribution frameworks


• Experience creating analytics data models and transformations. We use dbt


• Experience using tools for product analytics. We use Mixpanel


• Experience with BI and visualization tools (e.g., Lightdash, Tableau, Looker, PowerBI) and using them to enable self-service insights. We use Lightdash


• Experience with customer segmentation, cohort analysis, and predictive modeling for customer lifetime value or churn


• Experience using MLOps to ensure analyses and models are stable, repeatable, and maintainable


• Familiarity with marketing platforms and data sources (e.g., Google Ads, Facebook Ads, email marketing tools, CRM systems). We use Active Campaign and Salesforce


• Experience with distributed computing frameworks like PySpark or Dask

Why Join AoPS

This is a hybrid full-time position based at our headquarters in San Diego, CA. The full salary range for this position is 137.8k–169.6k. Here are some things you can look forward to:

• Impact: Transform marketing data into evidence-based insights that help us reach, engage, and retain the next generation of problem solvers


• Flexibility: Casual work environment with a hybrid work week and flexible scheduling


• Benefits: Multiple options for Medical, Dental, and Vision plans


• Future Planning: 401(k) with company match


• Quality of Life: PTO Plan and supportive leadership that gives you the work-life balance you deserve


• Ease of Transition: Relocation bonus (if currently located outside of San Diego)

Background Check

Please note that employment is contingent on the successful completion of a background check.

Work Authorization

Please note that in order to be considered for this position you must be legally authorized to work in the US. We are unable to offer sponsorship, including STEM-OPT and H-1B.

About AoPS

Art of Problem Solving (AoPS) is on a mission to discover, inspire, and train the great problem solvers of the next generation. Since 2003, we have trained hundreds of thousands of the country's top students, including nearly all the members of the US International Math Olympiad team, through our online school, in-person academies, textbooks, and online learning systems. While our primary focus has been math for most of our history, through the years we have expanded our unique problem solving curriculum into more subjects, such as language arts, science, and computer science.