DataScientist

## Accountabilities Develop and manage end-to-end predictive models focused on customer lifetime value (LTV), retention, segmentation, revenue forecasting, and marketing performance optimization Partner with marketing and revenue teams to improve campaign effectiveness, identify high-value customer cohorts, and enhance targeting and bidding strategies Analyze user behavior, customer journeys, engagement trends, and conversion funnels to uncover growth opportunities and performance improvements Define, measure, and monitor key business metrics, KPIs, and success frameworks for products, features, and growth initiatives Build machine learning models for conversion prediction, churn analysis, engagement forecasting, and revenue optimization using statistical and predictive techniques Identify opportunities to automate decision-making processes and implement prescriptive analytics solutions across product and marketing functions Collaborate with data engineering teams to design scalable data pipelines that support machine learning workflows, model retraining, and real-time analytics Present analytical findings, recommendations, and strategic insights to stakeholders at all levels, including senior leadership Translate business challenges into structured analytical projects and convert complex data findings into actionable business decisions Work cross-functionally with engineering, business intelligence, product, and marketing teams to deploy and scale data-driven solutions Requirements: Bachelor’s degree in Mathematics, Statistics, Computer Science, Engineering, Data Science, or another quantitative discipline 5+ years of experience in data science, growth analytics, decision science, or related analytical roles Strong proficiency in Python, including libraries such as Pandas, NumPy, and Scikit-learn Advanced SQL skills with experience querying and analyzing large datasets Hands-on experience with business intelligence and visualization platforms such as Tableau, Looke