Lead Data Analyst, Devices (Experimentation)

Life360

8h•$133,000 - $195,500•Remote

About The Position

We are seeking a Lead Data Analyst to play a pivotal role in shaping the future of the Life360 ecosystem, with a strong emphasis on pricing strategy, experimentation, and monetization. As an integral part of the Analytics team, you will work closely with Product Management, Growth and the leadership team to help define our Device short/long term strategy. Your role will focus on identifying new business opportunities and enhancing organizational value through data analysis, experimental design, and collaboration with cross-functional partners. This role is centered on unlocking revenue growth through rigorous pricing optimization, monetization modeling, and high-impact experimentation. Utilizing your skills in analytics and technical proficiency, you will leverage our distinct geolocation, mobile app, hardware and sales data to tackle key questions about business strategies and product effectiveness. Your mission includes not only daily analytical tasks but also contributing to strategic decisions that shape our product direction. The ideal candidate is motivated by the potential of data to influence product development and drive business growth, adept at translating complex data into actionable insights and strategic narratives. With a strong foundation in data analysis, technical skills, and a keen understanding of the product landscape, you'll be pivotal in guiding our product strategy.

Requirements

8+ years of experience in data analytics within consumer internet or mobile B2C environments, with direct ownership of growth and monetization outcomes.
Deep experience in subscription-led and hybrid monetization models (e.g., subscription + hardware, ecommerce add-ons), including pricing and attach optimization.
Demonstrated expertise in pricing strategy, including designing pricing experiments, modeling price-demand elasticity, optimizing promotions and bundles, and evaluating long-term revenue and margin impact.
Deep understanding of subscription economics in a B2C context, including LTV modeling, retention dynamics, attach rate optimization, churn analysis, and cohort-based profitability.
Strong experience applying Bayesian experimentation and hierarchical modeling techniques, particularly in low-traffic or high-uncertainty environments, enabling faster and more reliable decision-making.
Proven ability to partner cross-functionally with Product, Sales, Marketing, Finance, and Engineering to drive data-informed strategy and influence high-stakes decisions without direct authority.
Advanced proficiency in SQL and Python or R, with strong statistical foundations (causal inference, experimental design, regression modeling, forecasting). Experience working with cloud data platforms such as AWS, Snowflake, Databricks, Redshift, Presto, Athena, Hive, or Teradata.
Experience working with Big Data environments and modern analytics stacks, along with strong data visualization and storytelling skills using tools such as Tableau, Looker, Mode, Amplitude, Jupyter, or Excel.
Demonstrated ability to translate ambiguous business problems into structured analytical frameworks and actionable strategies that materially impact growth and profitability.
Excellent executive communication skills, with the ability to distill complex quantitative insights into clear narratives for both technical and non-technical stakeholders.
Strong project leadership skills with a track record of independently driving complex analytics initiatives from problem definition through implementation and business impact.

Responsibilities

Drive Device growth through rigorous, data-driven insights that deeply connect product, pricing, and customer behavior
Translate complex analyses into clear, actionable recommendations for senior leadership.
Establish and govern a unified metrics framework across Devices and Monetization, defining canonical KPIs
Champion a culture of experimentation by designing and analyzing A/B tests and quasi-experiments that unlock growth, improve conversion, and enhance user experience.
Ensure cross-functional alignment on metric definitions, and maintain trusted source-of-truth datasets for experimentation and executive reporting.
Lead pricing and experimentation initiatives, including price point testing, promotions, bundling, and subscription attach optimization.
Quantify incremental revenue, margin impact, and long-term LTV effects.
Build and maintain price-demand elasticity models to inform pricing, promotional, and portfolio decisions.
Apply Bayesian experimentation and hierarchical modeling techniques, particularly in low-traffic environments (e.g., new hardware launches, geo pilots), to improve speed and confidence of decision-making.
Use causal inference and econometric methods to simulate revenue and contribution margin under different scenarios.
Develop scalable monetization frameworks (e.g., Devices LTV, cohort profitability models) to support sustainable growth and margin expansion.
Partner with Data Engineering to improve data quality, experimentation infrastructure, and self-serve analytics capabilities across the organization.
Serve as a thought leader in Analytics, elevating statistical rigor and advancing Life360’s data-driven culture internally and externally.

Benefits

Competitive pay and benefits.
Medical, dental, vision, life and disability insurance plans (100% paid for US employees). We offer 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.

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