Senior Data Scientist, AI Native (Growth)
New
Within the US and CanadaFull-TimeSenior
Salary129000 - 190000 USD per year
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Job Details
- Experience
- 4+ years
- Required Skills
- AWSPythonSQLMachine LearningPyTorchPandasSparkTensorflowA/B testingDatabricksscikit-learn
Requirements
- 4+ 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.
- Experience with product development or customer life cycle management.
- Strong business acumen with the ability to translate data insights into actionable business strategies.
- Excellent communication and leadership skills, with the ability to influence cross-functional teams.
- Bachelor's degree in Data Science, Computer Science, Statistics, Mathematics, or a related quantitative field.
Responsibilities
- Design and implement scalable A/B tests to train 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.
- Collaborate with product managers and engineers to conceive and develop innovative product ideas, driving feature iteration and development to make impact.
- 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, data-driven decision-making, and agentic AI (AI-Native) best practices.
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