Growth Data Scientist (Statistical modeling)

Responsibilities

• Apply expertise in statistical modeling, causal inference, and Bayesian methods to analyze large-scale and complex datasets, uncovering valuable insights and patterns.
• Design and implement experiments, including A/B tests, to measure the impact of different strategies, initiatives, and product changes on user behavior and business outcomes.
• Develop predictive models and machine learning algorithms to identify key drivers of user behavior, optimize acquisition and retention strategies, and inform decision-making.
• Build media mix models to evaluate the effectiveness of various marketing channels and allocate budgets for optimal performance.
• Forecast customer lifetime value to support marketing strategies, customer segmentation, and retention initiatives.
• Utilize advanced statistical techniques, such as causal models, to understand the impact of different variables on user behavior and inform growth strategies.
• Effectively communicate complex findings and insights to both technical and non-technical stakeholders through clear visualizations, reports, and presentations.
• Stay up-to-date with the latest advancements in statistical modeling, machine learning, causal inference techniques, and digital marketing analytics, applying them to drive continuous improvement in our growth initiatives.

Requirments

• 1-3 years of experience in a related role with a deep understanding of causal inference methodologies and Bayesian modeling.
• Bachelor’s degree in Statistics, Economics, or a related quantitative field.
• Proven experience or knowledge in concepts such as media mix modeling, customer lifetime value forecasting, A/B testing, and causal models.
• Proficiency in programming languages such as Python or R for data manipulation, analysis, and modeling.
• Experience working with large-scale datasets, data visualization tools, and SQL databases.
• Solid understanding of experimental design and A/B testing methodologies.
• Excellent problem-solving skills and the ability to work both independently and collaboratively in a team environment.
• Strong communication skills with the ability to convey complex concepts to both technical and non-technical stakeholders.
• Experience in the growth or marketing analytics domain is highly preferred.