RESPONSIBILITIES:

• Develop and implement predictive models and advanced analytics to understand customer behavior, lifetime value, and churn.
• Utilize statistical and machine learning techniques to optimize marketing campaigns and personalization efforts.
• Develop and refine customer segmentation models to enable targeted marketing efforts.
• Develop and refine attribution models to understand the impact of different marketing channels and touchpoints on customer conversion and validate the model accuracy.
• Optimize budget allocation on paid channels to maximize ROI.
• Identify and model key High-Value Actions (HVAs) using causal inference that drive increased customer engagement and repeat purchases.
• Design, execute, and analyze A/B tests and other experiments to validate hypotheses and inform growth strategies.
• Work closely with engineering, product, and marketing teams to integrate data-driven insights into decision-making processes.
• Partner with data engineering teams to ensure the availability and quality of data required for analysis.
• Stay up to date with the latest trends, tools, and best practices in growth marketing and data science.

NEEDED SKILLS:

• MS or PhD in statistics, mathematics, engineering, computer science, economics or another quantitative field
• 5+ years of experience as a growth data scientist in relevant industry
• Hands-on experience applying machine learning, predictive modeling, causal inference to drive growth
• Strong problem-solving skills with the ability to think critically and strategically about business challenges
• Proficient in Python and SQL
• Excellent communication and presentation skills
• Experience with BI platforms such as Looker, Tableau etc.
• Move fast, be a team player, and kind

DEEP KNOWLEDGE IN:

• Statistical and machine learning techniques, and causal inference
• Data Science libraries in a programming or scripting language
• Growth and digital marketing