Data Analyst

Root is a fast-growing tech startup and we're on a mission to build the future of insurance.

As a Data Analyst in the engineering / analytics team at Root, your mission is to translate engineering, operational, and financial data into actionable insights that enable data-driven decisions across product, billing, risk, operations, and growth. You'll deliver high-impact dashboards, analyses, and metrics that drive Root's performance, improve product and service quality, and support strategic decision-making.

You'll partner closely with data engineers, finance, client teams and senior leadership to ensure data is not only available and correct, but interpreted in ways that drive measurable business outcomes.

1. Analytical Infrastructure & Tools
Design, build, and maintain analytical data models and metric logic.
Partner with Data Engineering to ensure upstream data integrity.
Maintain metric definitions and documentation (data dictionary, lineage).

2. High-Impact Analyses & Insights
Conduct deep-dive analyses on key business drivers (pricing, collections, conversions).
Deliver analyses with clear narratives and recommendations.
Support strategic initiatives such as product launches and pricing experiments.

3. Dashboards, Reporting & Visualization
Build and maintain internal dashboards.
Apply visualisation best practices and ensure reports are performant and intuitive.

4. Enablement & Self-Service
Develop self-service analytics tools for non-technical teams.
Document analytical processes and provide stakeholder training.

5. Data Governance & Quality
Leverage data pipeline and warehouse infrastructure.
Implement validation and anomaly-detection checks to ensure data trust.
Audit and reconcile data sources; resolve discrepancies with Engineering.
Follow compliant data handling practices adhering to Root practices.

6. Cross-Functional Collaboration & Communication
Translate business questions into analytical requirements.
Present findings clearly to both technical and non-technical audiences.
Foster a data-informed culture throughout Root.

7. Scalability & Efficiency
Identify repetitive analytical tasks and automate them.
Optimize queries and dashboards for performance and cost.

• Bachelor's degree in Statistics, Data Science, Economics, Accounting, Actuarial Science, Engineering, or similar. 
• 2–5 years' experience in data analysis, BI, or analytics roles. 
• Experience working with large datasets and modern data stacks. 
• Proficiency building and automating dashboards and reports. 
• Bonus: insurance, fintech, or billing domain exposure.

Technical / Analytical Skills

• SQL: complex queries, window functions, performance tuning, materialized views
• Statistics & Analysis: hypothesis testing, regression, forecasting, A/B testing.
• BI / Visualization Tools: Looker, Tableau, Power BI (or similar).
• Data Modeling & Warehousing: dimensional modeling, star schemas, Kimball.
• Automation & Tooling: familiar with DBT, Airflow, AWS Glue, or similar.
  Advantageous:
• Python / R: data munging, automation, basic statistical modeling.

Our mission is to enable innovation in insurance by building the infrastructure required to reach the future of insurance. We are striving to be the global API standard for insurance.

• Lead by example: "Lean in, take charge, and always set a positive precedent."
• Exceed expectations: "Know your customer to delight your customer."
• Rally as one team: "Put aside egos and personal agendas to triumph as one."
• Own the mission: "Your job is not done until the job is done."
• Rise to the challenge: "Meaningful change requires meaningful effort and the courage to make bold moves."

Our team is made up of smart, passionate, and kind individuals working together to build a world-class business. We take the time to develop personal relationships with each other. Over and above daily team lunches, we do frequent team outings and ad-hoc adventures (when global pandemics permit).

We create and enable an environment for people to do their best work. To support this, we focus on a culture of autonomy, transparency and trust. As a startup, we care a lot about innovation, and believe in an iterative way of working to drive innovation forward. We encourage each other and foster a working culture of sharing early versions of our work and implementing feedback fast.