Staff Data Scientist - Ads (AI Native)
New
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Life360Data Science, Machine Learning, Advertising
Remote, USA ; Remote, CanadaFull-TimeStaff
SalaryFor candidates based in the US, the salary range for this position is $137,000 to $252,000 USD. For candidates based out of Canada, the salary range for this position is $198,000 to $233,000 CAD.
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Job Details
- Experience
- 8+ years
- Required Skills
- PythonSQLCloud ComputingKubeflowMLFlowAirflowdbtMLOpsPySpark
Requirements
- Advanced degree in a quantitative field or equivalent industry experience.
- 8+ years of experience analyzing, implementing, and operating machine learning and/or optimization systems.
- Strong proficiency in Python with deep familiarity with software engineering best practices.
- Familiarity with ML lifecycle and data processing tools such as MLflow, Kubeflow, SparkML, Synapse ML, SQL, Spark/PySpark, dbt, and Airflow.
- Practical experience operating within a major cloud ecosystem (e.g., AWS, GCP, Databricks).
- Clear grasp of cloud networking, security, and storage tiers.
- Strong communication and project leadership skills with the ability to influence cross-functional teams.
- Ability to structure ambiguous problems precisely.
- Experience formulating and solving optimization problems (e.g., linear programming, mixed-integer programming) is a plus.
Responsibilities
- Partner with Product, Data Science, Cloud Engineering, and Data Engineering to design, develop, and deploy machine learning and optimization solutions.
- Train, deploy, and scale machine learning models as high-availability microservices or batch processing workflows.
- Establish unified logging, alerting, and monitoring solutions to track model inference performance, system latency, resource utilization, data drift, and concept drift.
- Implement robust lineage tracking for data, code, and algorithmic artifacts to ensure compliance, reproducibility, and security.
- Work with data engineering to improve the data ecosystem, ensuring robust, scalable pipelines for experimentation and ML.
- Mentor other Data Scientists and help define best practices and technical architectures for machine learning engineering and scalable ML service ops.
- Use agentic AI tools (Claude Code or equivalent) as a core part of your daily workflow.
- Handle on-call rotation and address live production incidents.
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