Senior Data Scientist I

DUTIES: The Senior Data Scientist I is responsible for performing a variety of statistical analysis and machine learning tasks, ranging from designing and evaluating experiments, conducting research, developing predictive and causal models, building marketplace optimization algorithms, to informing decision-making through insights, data storytelling, and reporting. This role collaborates closely with diverse teams (including product managers, engineers, and fellow data scientists) to advance our understanding of the customer, make predictions to improve our products and experiences, apply causal inference methods, and design and measure experiments.

Specific duties include: (1) utilize strong technical expertise and develop a thorough understanding of our data to drive insights in the areas of customer acquisition, engagement, retention, and loyalty through causal inference and experimentation methods; (2) contribute to organizational maturity in data storytelling and best-in-class ML and statistical approaches; (3) design product experiments to test business hypotheses, apply rigorous statistical analyses, and interpret the results to draw impactful insights; (4) drive clarity and solve ambiguous business problems using data-driven approaches; (5) contribute to the data science roadmap and priorities within area of ownership; (6) utilize experience with exploratory data analysis, statistical analysis and testing, experiment design and model development, and knowledge of how to leverage these skills to solve complex business problems; (7) apply advanced causal inference methods, including treatment effect estimation, counterfactual analysis, and advanced causal machine learning approaches such as Double Machine Learning, Meta-Learners and Causal Forests, to evaluate the impact of product features, policies, or business strategies; (8) work in Python and utilize data analysis and machine learning, including Pandas, Numpy, LightGBM, Scikit-Learn, PyTorch, and causal inference libraries including EconML and Statsmodels; (9) utilize data visualization tools, including Tableau, to communicate analytical results and business insights; (10) consult with internal teams regarding model performance and translate analytical findings into actionable insights and decision strategies; and (11) apply statistical analysis and machine learning techniques to develop predictive models and solve complex business problems. Telecommuting available from anywhere in US. HQ at 420 20th St N, Suite 100, Birmingham, AL 35203.

MINIMUM REQUIREMENTS: This position requires a Master’s degree or equivalent in Data Science, or Mathematics and 3 years of experience working with statistical analysis and machine learning. Must also have 24 months of experience with each of the following: (1) apply advanced causal inference methods, including treatment effect estimation, counterfactual analysis, and advanced causal machine learning approaches such as Double Machine Learning, Meta-Learners and Causal Forests, to evaluate the impact of product features, policies, or business strategies; (2) apply statistical analysis and machine learning techniques to develop predictive models and solve complex business problems; (3) work in Python and utilize data analysis and machine learning, including Pandas, Numpy, LightGBM, Scikit-Learn, PyTorch, and causal inference libraries including EconML and Statsmodels; (4) consult with internal teams regarding model performance and translate analytical findings into actionable insights and decision strategies; and (5) utilize data visualization tools, including Tableau, to communicate analytical results and business insights. Employer will accept experience gained concurrently. Telecommuting available from anywhere in US. HQ at 420 20th St N, Suite 100, Birmingham, AL 35203. Salary: $123,000 to $247,000/year. Full-time position. Please go to our website for benefits information and to apply: https://www.shipt.com/careers/ or apply by email at careers@shipt.com.

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