Pie's mission is to empower small businesses to thrive by making commercial insurance affordable and as easy as pie. We leverage technology to transform how small businesses buy and experience commercial insurance.
Like our small business customers, we are a diverse team of builders, dreamers, and entrepreneurs who are driven by core values and operating principles that guide every decision we make.
Pie is building a Claims Department where data, analytics, and technology will play a key role in achieving our goal of making small business insurance as easy as Pie. The ideal candidate will have a combination of strong technical skills in data analysis, data visualization, and predictive modeling and a strong understanding of Workers' Compensation insurance claims. Initially, the successful candidate will focus on working with Claims business team to create repeatable ad hoc reports to measure key performance indicators for high level objectives as well as basic operational metrics. Concurrently, this role will collaborate with our data engineering team to build the data infrastructure necessary for data warehouse reporting and analysis. This is a rare opportunity for an analyst to strongly influence data collection, storage, and organization from the ground up and ensure that data documentation is accurate and complete to facilitate their future analyses. Predictive Modeling, decision management, and claims process automation will become a growing part of this role as more data is accumulated and the claims department matures. The successful candidate must be a quick learner, and be comfortable with ambiguity and working in a "build" environment.
How You’ll Do It
- Data Visualization and Reporting
- Mines data, performs quantitative analysis and creates clear and actionable narratives about the business.
- Turn data into visualizations to create a comprehensive picture of results and trends.
- Extract data from Pie's data warehouse or other sources, such as claims software and enterprise dashboards, for ad hoc reporting requests and larger projects
- Create dashboards, ad hoc reports, and data visualizations for high level analysis as well as basic operational reporting needs
- Work with Claims leadership to develop reporting for key performance metrics
- Data Analysis
- Analyze complex business problems and issues using data from internal and external sources to provide insight to decision-makers.
- Develop new data analysis processes, including data collection and data governance.
- Perform predictive analytics by reviewing large data sets of historical data, including market trends, financial data and operational metrics. This data will then be used in the future to build predictive models that can generate forecasts and risk assessments to reduce exposures.
- Create models and tools that produce relevant insights to identify inefficiencies and generate insights to improve workflow processes
- Analyze data to identify drivers of claim outcomes, investigate ways to reduce claim severity and improve the operational efficiency of the claims department.
- Benchmark claim department results against external data sources
- Business Acumen
- Understanding of the insurance industry's key metrics, challenges and what drives success.
- Ability to align data and analytics with overall business goals
- Proficiency in communicating complex data insights in a clear and actionable manner to stakeholders across the organization.
- Collaboration
- Offers recommendations for new data analytic techniques and methodologies
- Support other strategic projects as assigned to meet business needs
- Serve as the subject matter expert on claims data
- Collaborate with Claims leadership, as well as Data Science, Data Engineering, and Enterprise Engineering, to create data warehouse reporting capabilities, predictive models, automation, and data mapping for vendor integrations.
The Right Stuff
- SQL Programming, preferably in a Cloud environment
- Statistical Programming Language- experience with at least one - Python (Pandas and data analysis packages), R, SAS, SPSS, Stata
- Extracting and manipulating large data sets using Snowflake, Looker, and Montecarlo platforms.
- Understanding of data capture, data mapping, and data cleansing.
- Strong understanding of workers' compensation claims process, terminology, and metrics.
- Ability to draw meaningful insights from data. Ability to perform basic statistical analysis.
- Experience using Looker, Tableau, or similar data visualization tools
- Comfortable using Excel and Google sheets for interim reporting needs
- Self-motivated, flexible, organized who is interested in performing exploratory data analysis with complex data sets with minimal direction
Seeking innovative solutions through data and analytics while being adaptable to new tools and technologies
Base Compensation Range
$125,000 - $160,000 USD
Compensation & Benefits
- Competitive cash compensation
- A piece of the pie (in the form of equity)
- Comprehensive health plans
- Generous PTO
- Future focused 401k match
- Generous parental and caregiver leave
- Our core values are more than just a poster on the wall; they’re tangibly reflected in our work
Our goal is to make all aspects of working with us as easy as pie. That includes our offer process. When we’ve identified a talented individual who we’d like to be a Pie-oneer , we work hard to present an equitable and fair offer. We look at the candidate’s knowledge, skills, and experience, along with their compensation expectations and align that with our company equity processes to determine our offer ranges.
Each year Pie reviews company performance and may grant discretionary bonuses to eligible team members.
Location Information
Unless otherwise specified, this role has the option to be hybrid or remote. Hybrid work locations provide team members with the flexibility of working partially from our Denver office and from home. Remote team members must live and work in the United States* (*territories excluded), and have access to reliable, high-speed internet.
Additional Information
Pie Insurance is an equal opportunity employer. We do not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity, marital status, age, disability, national or ethnic origin, military service status, citizenship, or other protected characteristic.
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