Zinnia is simplifying how people buy, sell, and administer insurance products. Combining intuitive enterprise technology solutions and data insights, the Policygenius marketplace, and market-leading products including smartoffice, annuitynet, lifespeed, winflex, TPP, vitalsales Suite, and Exchange Consulting, Zinnia is redesigning the insurance experience for shoppers, advisors, and insurers alike — and enabling more people to protect their financial futures along the way. Zinnia has over $173.7 billion in assets under administration across 100+ carrier clients, 2500 distributors and partners, and over 2 million policyholders.
WHO YOU ARE: Our data team serves Zinnia through data engineering, data analysis, and data science. Our goal is to help uncover opportunities and make decisions with data. We partner with all department stakeholders across the company to develop deeper predictors of behavior, develop insights that drive business strategy and build solutions to optimize our internal and external experiences.
WHAT YOU'LL DO: Work collaboratively with the Life & Annuity product team and assist them on the three fronts of analytics: monitoring and measurement, research and experimentation and help drive the analytics roadmap.Drive analytical projects such as product feature discovery, user segmentation/targeting strategies and product vision strategies.Help our teams move beyond visualizations and utilize inferential and causal modelling to uncover deeper trends from a quantitative perspective, and design and test interventions.Create visualizations intended to monitor business performance or uncover interesting trends to investigate.Lead the test and learn process for exploratory data analysis and A/B testing. This includes helping stakeholders decide on testing strategy, generating baselines, approximating sample sizes and performing analysis of test results.Partner with data engineering on new data pipelines and ingestion requests as well as advise on data model improvements.Wrangle and stitch together many disparate data sources and uncover deep insights to drive your team forward.Mentor data analyst team members and learn from data scientists to advance into predictive and algorithmic solutions.Drive data analysis code best practices and analysis standards.WHAT YOU'LL NEED: You have 5+ years of analytics/product analytics experience focused on analyzing data centered around user behavior, customer segmentation and product feature evaluation.You have experience consolidating data from various data sources and familiarity with events tracking management.You are proficient with analytics platforms and code in R or Python, use SQL/relational cloud databases efficiently.You have experience with web analysis such as creating product funnels, user behavior, and paths.You have experience with designing and analyzing experiments including but not limited to A/B testing.You understand business metrics such as CAC, LTV, Conversion Rates and can apply them to your decision making and prioritization as well as creating and managing analysis frameworks.You understand statistics and base models such as linear and logistic regression, segmentation methods, time series analysis, outlier and anomaly detection, categorical data analysis, and causal impact modelling.You are well-versed in product techniques, product discovery process and product metrics such as cohort analysis, funnel analysis and experimentation.You have experience with relational cloud databases like Redshift, BigQuery, Snowflake, but you are also comfortable working with unstructured files and datasets.WHAT'S IN IT FOR YOU? At Zinnia, you collaborate with smart, creative professionals who are dedicated to delivering cutting-edge technologies, deeper data insights, and enhanced services to transform how insurance is done. Visit our website at www.zinnia.com for more information. Apply by completing the online application on the careers section of our website. We are an Equal Opportunity employer committed to a diverse workforce. We do not discriminate based on race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability.
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