Translate complex datasets into clear insights with strategic recommendations that drive measurable actions and outcomes to inform product direction and business priorities
Partner with Product and Operations teams to define KPIs and lead the analytics strategy for key product areas, including causal inference, cohort analysis, retention modeling, and experimentation design
Develop forecasts for ARR, conversion, churn, and usage using economic and behavioral data
Collaborate with data engineering, analytics, and product to shape best practices in experimentation, forecasting, and decision support
Frame business questions into well-scoped analytical or modeling problems, especially those with strategic or monetization impact
Apply advanced statistical and econometric techniques (including causal inference and forecasting) to analyze business problems
Create compelling data narratives that drive decisions about product, pricing, growth, and retention
Set standards and best practices for KPIs, metrics, and experimentation across the company
Foster a culture of data-driven decision making through strong analytical rigor and communication

Graduate-level research experience on data-intense problems or 1+ years of industry experience in machine learning or economics-focused roles
A blend of economic theory, applied econometrics, and business skills that let you jump into a fast-paced environment and contribute from day one
Proven ability to identify and measure causal business impacts using appropriate statistical techniques, especially in complex or observational settings
Strong engineering skills with expertise in R or Python and fluency in data manipulation (SQL, Pandas) and machine learning (scikit-learn, XGBoost, Keras/TensorFlow) tools
Ability to identify and prioritize high-impact problems and deliver solutions that balance urgency and quality
Strong verbal and written communication skills – ability to distill complex findings from models and economic reasoning into compelling insights and communicate effectively with technical and non-technical audiences.

Data Scientist, Economist

Key skills