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
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