Contribute to the development of customer segmentation models using clustering and unsupervised learning techniques to uncover behavioral cohorts and inform targeting.
Build and refine forecasting models (e.g., ARIMA, Prophet, ML-based time series methods) to predict demand and engagement trends.
Support efforts in modeling customer value over time (LTV) and assist in translating findings into practical strategies for acquiring and retaining customers.
Develop churn prediction models to identify at-risk users and propose interventions in partnership with product and marketing teams.
Create scalable, reusable ML workflows and data science artifacts that improve efficiency across the org.
Partner with analysts and engineers to design and interpret experiments (A/B tests, cohort studies, causal inference).
Present insights and model outcomes clearly to technical and non-technical audiences, bridging the gap between data and decision-making.
Requirements
5+ years of experience in data science or advanced analytics, ideally within eCommerce, digital subscriptions, or marketplaces.
Strong proficiency in Python and SQL for data manipulation, modeling, and analysis.
Familiarity with Databricks or similar cloud-based data platforms.
Solid understanding of time series forecasting methods (ARIMA, Prophet, ML-based).
Experience building segmentation or clustering models (e.g., k-means, hierarchical clustering, embeddings).
Strong applied statistics foundation (hypothesis testing, regression, experimental design).
Proficiency with data visualization tools (e.g., Tableau, Power BI, or equivalent).
Demonstrated ability to manage projects independently, while working effectively with partners from different functions.
Benefits
Pay within this range varies by work location and may also depend on job-related knowledge, skills, and experience.
Non-sales roles starting salaries are expressed as base salary and short-term incentives are in the form of the Annual Incentive Plan (AIP).
Certain roles may be eligible for long-term incentives in the form of a new hire equity award.
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Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard skills
customer segmentation modelsclustering techniquesunsupervised learningforecasting modelsARIMAProphetML-based time series methodschurn prediction modelsdata manipulationdata analysis