At AoPS, data sits at the heart of how we grow and deliver our mission. We serve tens of thousands of students around the world, generating data about how families discover us, how students learn, and how our operations scale. Yet, like our curriculum and teaching, the true value of our data comes from how well we can translate it into actionable insight. AoPS is unique because it brings together academics, operations, and technology under one roof. We design our own curriculum, run physical academies, deliver online courses, and build the platforms that power it all. This created a rich and complex data environment--one that grew organically as the business grew and we are working on creating a more cohesive stack so every business line runs on the same system. Your job will be to turn raw data into clear, actionable insights, while proactively identifying areas for improvement.
Requirements
- Proficiency in Python for data analysis, statistical modeling, and machine learning (using packages like pandas or polars for data manipulation, scikit-learn or statsmodels for model development, and PySpark or Dask for distributed computing).
- Experience using tools and best practices for reproducible research (e.g., version-controlled analysis, environment management, documented workflows) and with MLOps to ensure analyses and models are stable, repeatable, and maintainable.
- Strong understanding of concepts relevant to learning research, such as experimental design, hypothesis testing, feature engineering, regression modeling, causal inference, clustering, and evaluating data quality in educational or behavioral datasets.
- Experience using SQL data warehouses such as Redshift, Snowflake, or BigQuery to gather and transform data for analysis. We use Redshift and dbt.
- Experience using data visualization or BI tools like Lightdash, PowerBI, Tableau, or Looker. We use Lightdash.
Responsibilities
- Take ownership of learning analysis and applied research for the Academics department, ensuring analyses, models, and data tools are accurate and aligned with strategic goals.
- Partner with stakeholders to translate academic, curriculum, and product questions into testable hypotheses, measurable outcomes, and business decisions.
- Work with the data team to define, govern, and validate the metrics, features, and data structures needed to support consistent, science-driven analyses.
- Use SQL and Python to power analyses, modeling, reproducible research, and data-driven recommendations.
- Proactively investigate patterns and anomalies in learning data to uncover meaningful trends, identify drivers of student outcomes, and separate actionable insights from background noise.
- Champion data literacy and effective analytic practices across the organization.
Other
- 2-4 years of experience in data science, applied statistics, quantitative research, or similar analytical role with a track record of driving meaningful impact.
- Excellent communication skills with the ability to gather requirements from stakeholders, prioritize potential projects, and translate complex quantitative findings into actionable insights for the academics team.
- This is a hybrid full-time position based at our headquarters in San Diego, CA.
- Please note that employment is contingent on the successful completion of a background check.
- 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.
