What you’ll be doing
- Partner with marketing and insurance operations teams to understand business strategy, challenges and goals in efforts discover areas for optimization and opportunity.
- Deliver deep-dive analyses of marketing campaign and insurance carrier performance as well as ad-hoc requests to put forward hypotheses and recommendations for future initiatives and programs.
- Define metric calculations; partner with Data Engineer on development of self-serve dashboards to monitor KPIs and success metrics.
- Utilize proprietary and third-party tools (business intelligence platform, web analytics platforms and ad-serving technologies) to report and analyze product, customer, pricing and revenue data.
- Own customer acquisition channel reporting suite along with marketing and web analytics stack.
- Help evolve and strengthen marketing attribution through various lift analysis and beyond.
- Develop CRM & lifecycle cohort-based communication reporting and analytics practice.
- Drive sophisticated customer segmentation analysis and cohort level LTV modeling.
- Evaluate performance by customer, carrier, coverage, discounts and beyond to inform product and partner optimization.
- 2 to 3 years of experience in a quantitative focused analyst or analytics role in a fast-paced data-driven environment.
- Solid understanding of data technology and best practices (Hadoop/Hive/R/Python, etc.)
- Proficient in SQL and handling big data (experience with Python or other scripting languages a plus)
- Meticulous attention to detail with an ability to learn quickly.
- Experience in FinTech/InsurTech or products with complex data architectures.
- Solid understanding of multivariate testing, attribution modeling, media mix modeling, lift analysis, and customer segmentation highly preferred.
- Strong communication skills and the ability to explain complex analyses to both technical and non-technical audiences.
- Experience with and data visualization tools a must.
- Must be able to manage multiple projects and work with key stakeholders across different departments.
- Bachelor's degree in finance, math, statistics or economics preferred.