Staff Data Scientist - Ads (AI Native)

Life360

4d • $137,000 - $252,000 • Remote

About The Position

Life360 is seeking a Staff Data Scientist for their Ads team. This role involves deep analysis of technical problems in ads delivery, translating that analysis into algorithmic solutions, and working with engineers to implement, deploy, and operate these solutions. The position is within the Ads business unit, a core revenue line for Life360. The successful candidate will partner with other Data Scientists and engineers to enhance the scale and efficacy of ads served across the infrastructure. The team is scaling ads-optimization models and needs a senior specialist to lead this transition. Success in the first year includes taking at least one ads-optimization model from prototype to production and measurably improving a delivery metric at scale.

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 (testing, modularization, version control, etc.).
• Familiarity with specialized ML lifecycle and data processing tools and platforms 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—with a clear grasp of cloud networking, security, and storage tiers.
• Strong communication and project leadership skills, with the ability to influence cross-functional teams.
• Problem-solving mindset - You structure ambiguous problems precisely before reaching for a tool, AI or otherwise.
• Collaborative approach - You can explain technical tradeoffs and articulate ideas effectively, work well across teams, and value diverse perspectives.
• Ownership mentality - You take responsibility for your work from design through production and beyond.
• Daily use - You use AI tooling (Claude Code or equivalent) as a genuine development partner every day: delegating discrete implementation tasks, running parallel workstreams, and writing the prompts and specs that make that possible.
• Judgment and ownership - You review AI-generated code, analysis, and models critically before they ship, and you're accountable for what reaches production regardless of whether a human or an agent wrote it.
• Velocity - You're expected to turn AI fluency into real output leverage, shipping and iterating on ML models faster than a comparable team working without AI-native workflows.
• Team leadership - You share what you learn, surfacing effective prompts, workflows, and guardrails so the rest of DSML gets better at working with AI, not just you.
• Continuous learning - You stay current on agentic AI and ML tooling and bring concrete recommendations back to the team, rather than waiting for tooling decisions to be made for you.

Nice To Haves

• Hands-on experience formulating and solving optimization problems (e.g., linear programming, mixed-integer programming) for advertising use cases such as budget allocation, bid optimization, or audience targeting.

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, working with infrastructure and backend engineers to integrate model outputs directly into our ads systems.
• 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 across the entire development and operational lifecycle.
• 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 — delegating implementation tasks, running parallel workstreams, and critically reviewing AI-generated code and analysis before it ships.
• Handle on-call rotation and address live production incidents.

Benefits

• Competitive pay and benefits.
• Medical, dental, vision, life, and disability insurance plans (100% paid for US employees). Supplemental plans for medical and dental for Canadian employees.
• 401(k) plan with company matching program in the US and RRSP with DPSP plan for Canadian employees.
• Employee Assistance Program (EAP) for mental wellness.
• Flexible PTO and 12 company-wide days off throughout the year.
• Learning & Development programs.
• Equipment, tools, and reimbursement support for a productive remote environment.
• Free Life360 Platinum Membership for your preferred circle.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: Associate degree