Data Science at Policygenius...
Policygenius continues to disrupt the insurance industry by delivering innovative technology-driven experiences. We are advancing our tech capabilities and learning to leverage our hordes of data to develop innovative machine learning applications. We are relentless in our drive to reliably deliver outstanding products at scale. We are growing fast, but we can go further faster with experienced, collaborative, challenge-seeking analysts like yourself.
Our data team serves Policygenius through data engineering, data analysis and data science. Our goal is to help uncover opportunities and make decisions with data. We partner with Product, Design, Engineering, Marketing and numerous stakeholders across the company to develop deeper predictors of behavior and build solutions to optimize our internal and external experiences.
In this role, you will…
Work collaboratively with the CRM team and assist them on the three fronts of analytics: monitoring and measurement, research and experimentation, and to help drive the analytics roadmap
Drive analytical projects such as owned media optimization, targeting strategies, and campaign strategies
Help our teams move beyond visualizations and utilize inferential and causal modeling 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 we use 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
We’d love to hear from you if…
You have 5+ years of marketing analytics experience focused on analyzing data centered around customer retention, personalization, and campaign impact analysis
You have experience pulling data from third party sources such as Facebook and Google and can combine with internal data sources
You have familiarity with identity resolution providers and experience stitching third party data to first party pixel identification data
You are proficient with analytics platforms and code in R or Python, use SQL/relational cloud databases efficiently
You understand statistics and base models such as linear and logistic regression and segmentation methods and time series analysis, outlier and anomaly detection, categorical data analysis, and causal impact modeling
You are well versed with marketing techniques, consumer facing marketing and product metrics such as cohort analysis, LTV / CAC, and campaign optimization
You have experience with designing and analyzing experiments including but not limited to A/B and multivariate testing
You have experience with relational cloud databases like Redshift, BigQuery, Snowflake, but also comfortable working with unstructured files and datasets
You can expect...
Company-paid health, dental, vision, life & disability insurance
401(k) plan, FSA & commuter benefits
A flexible-first workplace, with the freedom to work in our beautiful offices or remotely as needed based on the needs of your role, team, and the business
The opportunity to grow alongside a company shaking up a big, old-fashioned industry, including training, mentorship and coaching from leadership
An inclusive community of fun, diverse, and open-minded coworkers committed to our mission of helping people get financial protection right
Technologies You Will Use
_Python or R _for machine learning algorithms and analysis.
Google Cloud Platform: Kubernetes, Cloud SQL, Cloud Functions, PubSub, BigQuery, DataStore, and more: we keep adopting new tools as we grow!
_Airflow _for data pipelining.
Tableau for data visualization and consumer facing dashboards.
Many more to come!