Data Scientist

Data Scientist

We are seeking a Data Scientist with expertise in experimentation, causal inference, and retention analytics to drive data-informed decision-making and optimize user engagement. In this role, you will design and analyze experiments (A/B tests, quasi-experiments), develop measurement frameworks for key metrics (DAU, WAU, MAU, retention), and provide actionable insights to improve product growth and user retention. Proficiency in PySpark is highly desirable to handle large-scale datasets efficiently.

Responsibilities include:

• Design, implement, and analyze A/B tests, multi-armed bandits, and quasi-experimental methods to measure the impact of product changes.
• Apply causal inference techniques (e.g., difference-in-differences, propensity score matching, synthetic control, regression discontinuity) to estimate treatment effects in non-randomized settings.
• Collaborate with product, engineering, and marketing teams to define hypotheses, success metrics, and statistical power requirements.
• Ensure rigorous statistical validity (e.g., controlling for biases, multiple testing corrections, confidence intervals).
• Develop and refine retention measurement frameworks (e.g., cohort analysis, survival analysis, churn prediction).
• Define and track core engagement metrics (DAU, WAU, MAU, rolling retention, N-day retention) and diagnose trends.
• Identify key drivers of retention through segmentation, funnel analysis, and predictive modeling.
• Work with growth teams to optimize onboarding, engagement loops, and monetization strategies.
• Build and maintain scalable data pipelines (using PySpark, SQL, or big data tools) to process and analyze large datasets.
• Develop automated dashboards and reports (e.g., Tableau, Looker, Metabase) to monitor experiment performance and retention trends.
• Ensure data quality and consistency in metric definitions across teams.
• Optimize queries and computations for performance and cost efficiency in distributed systems (e.g., Databricks, AWS EMR, GCP BigQuery).
• Partner with product managers, engineers, and marketers to translate business questions into data-driven analyses.
• Present findings and recommendations to executive stakeholders in clear, actionable formats.
• Mentor junior data scientists and analysts on best practices in experimentation and retention analytics.

Qualifications include:

• 3+ years of experience in data science, analytics, or experimentation (or equivalent in academic research).
• Strong background in statistics and causal inference (hypothesis testing, Bayesian methods, experimental design).
• Hands-on experience with SQL and Python (Pandas, NumPy, SciPy, StatsModels, Scikit-learn).
• Proficiency in experimentation tools (e.g., Optimizely, Statsig, Eppo, or custom in-house systems).
• Experience defining and analyzing retention metrics (DAU/WAU/MAU, cohort retention, churn).
• Familiarity with big data tools (PySpark, Hadoop, or similar distributed computing frameworks).

Highly desirable:

• Expertise in PySpark for large-scale data processing and analytics.
• Experience with time-series forecasting, survival analysis, or uplift modeling.
• Knowledge of ML for retention (e.g., propensity models, clustering, recommendation systems).
• Experience with data visualization tools (Tableau, Looker, Plotly, Matplotlib/Seaborn).
• Background in growth analytics, product analytics, or marketing analytics.

Nice to have:

• Advanced degree (MS/PhD) in Statistics, Economics, Computer Science, or a quantitative field.
• Experience with reinforcement learning or bandit algorithms for dynamic experimentation.
• Knowledge of MLOps or productionizing models (e.g., MLflow, Airflow, Docker).

What we offer:

• Competitive compensation and equity aligned to the markets where our team members are based.
• Comprehensive health and wellness benefits, including medical, dental, vision, and additional support programs.
• The opportunity to work on cutting-edge AI with a small, mission-driven team.
• A culture that values transparency, trust, and community impact.

Come help build the space where anyone can explore and help shape the future of AI.

Arena Intelligence provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability, genetics, sexual orientation, gender identity, or gender expression. We are committed to a diverse and inclusive workforce and welcome people from all backgrounds, experiences, perspectives, and abilities.