Apply data mining and modeling skills to problems in areas such as Real Estate & Design and/or Transportation.
Build ML models and partner with Engineering to productionize results in tools and data pipelines.
Utilize visualization and storytelling skills to drive data-driven decision-making.
Working knowledge with SQL, Hive, Presto and big data systems and tools
Working experience in Python, R, etc for data exploratory analysis and machine learning models.
Experienced with end-to-end data science projects in time series forecasting, clustering regression or classification using at least two of the following algorithms: ARIMA, Linear Regression, decision trees, random forest, XGBoost, logistic regression, K-Means, DBSCAN.
Understanding of modeling fundamentals and best practices (e.g., feature selection, Bias-Variance Tradeoff)
Demonstrated experience in applying statistical and/or algorithmic approaches to solving real-world problems
Experience in communicating model results to leadership and cross-functional team members.
4-9 years of experience
Bachelor's degree in a quantitative field such as Statistics, Mathematics, Economics, Computer Science, Quantitative Finance, Math, Physics or a related Engineering degree