Senior Data Scientist AI Native (Growth)
New
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Life360Mobile App, Consumer Tech
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
- Experience in subscription-based products, lifecycle marketing, or user acquisition (Preferred)
- Experience with geospatial data and mobile location-based services (Preferred)
- Familiarity with Bayesian modeling, uplift modeling, and reinforcement learning for experimentation (Preferred)
- Experience with workflow automation tools for experimentation and data science operations (Preferred)
- Experience in the consumer technology sector (Preferred)
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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