Lead Data Analyst

Posted 2 days agoViewed

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💎 Seniority level: Lead, 6+ years

📍 Location: United States

💸 Salary: 147500.0 - 216500.0 USD per year

🔍 Industry: SaaS / consumer app

🗣️ Languages: English

⏳ Experience: 6+ years

🪄 Skills: SQLData AnalysisTableauProduct AnalyticsData engineeringCommunication SkillsAnalytical SkillsData visualizationData modelingData analyticsA/B testing

Requirements:

6+ years of experience as an analyst, data scientist, or BI Engineer.
4+ years of SaaS / consumer app experience and understanding of related metrics.
Expert capabilities with SQL and Tableau are required.
Experience with Python is a plus, as is experience with other data access and visualization tools.
Degree in Computer Science, Math, Physics, Engineering, Finance, or another quantitative field.
Proficiency in Excel and a strong familiarity with advanced functions.
Strong written and verbal communication skills, and comfort interacting with executives.
Experience in communicating to both technical and non-technical audiences.
The ability to thrive in a dynamic environment.
Ability to work collaboratively across different functions and effectively influence senior business partners.
Strong analytical, problem-solving, and critical thinking paired with intellectual curiosity and aptitude in picking up new technical skills.
Curiosity to learn about new topics and uncover hidden insights.

Responsibilities:

Own and enhance existing user growth and onboarding dashboards. Identify and fill gaps in our understanding of product growth.
Work with business leaders to define key metrics and build reporting to monitor and understand performance along those metrics.
Generate insights that steer our Product testing roadmap.
Design, measure, and scale Product A/B tests.
Identify and solve issues with data availability, consistency, and quality.
Identify and find solutions for operational use cases e.g. system monitoring and alerting, outlier detection, etc.
Create and deliver impactful presentations that tell a story focused on insights, not just data.
Remain detail-oriented while working across a wide variety of projects.
Work with Data Engineering to design data pipelines that help organize relevant data towards a single source of truth.
Work with Data Science on predictive models for what experiences and attributes affect a user's quality with Life360.
Forecast growth KPIs, identify opportunities, influence business partners, and drive effective decision-making.
Partner with Product, Marketing, Engineering, and Finance teams to help resolve broader business problems, create growth plans, establish financial and operating targets, and determine optimal resource requirements.
Be part of a great team, while also being capable of operating independently - managing relationships, deliverables and expectations with your business partners.

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