Lead Data Scientist, Growth

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Requirements:

• 8+ years of experience in data science, machine learning, or analytics, with a focus on growth, experimentation, and user retention.
• Strong experience in causal inference, A/B testing methodologies, and statistical modeling.
• Deep understanding of machine learning models for user segmentation, personalization, and predictive analytics.
• Proficiency in Python (Pandas, Scikit-learn, PyTorch, or TensorFlow) and SQL for data manipulation and analysis.
• Experience with big data technologies such as Spark, AWS, Databricks.

Responsibilities:

• Design and implement scalable A/B testing, causal inference models, and multi-armed bandits to optimize registration, trial conversion, and retention strategies.
• Build and scale automation tools for experimentation and segmentation, ensuring teams can efficiently test and iterate on hypotheses.
• Develop predictive models and statistical frameworks to improve trial-to-subscription conversion, reduce churn, and enhance overall customer LTV.
• Leverage clustering, behavioral analysis, and geospatial data to identify key user segments and tailor experiences accordingly.
• Partner closely with growth, lifecycle marketing, and user acquisition teams to translate insights into scalable marketing and product strategies.
• Work with data engineering to improve the data ecosystem, ensuring robust, scalable pipelines for experimentation and analysis.
• Act as a mentor and thought leader within the data science team, helping to define best practices in experimentation, machine learning, and data-driven decision-making.