Analytics Engineer

As an Analytics Engineer, you will be a prolific individual contributor to our pipelines, tables, and data models that enable analytics and reporting to the rest of the organization. You will help bridge the gap between Data Engineering, the broader Data & Analytics team, and the rest of the business by leveraging both your technical expertise and understanding of business goals.

Your specific tasks include:

Building and managing reporting data models and infrastructure in Snowflake and related ETL / data engineering tools
Building basic reports for all major stakeholders (underwriting, data entry/operations, claims) in Looker
Training team members on how to leverage and/ update data models as necessary
Building automation related to reporting, such as monthly bordereaux (monthly reports sent to carriers)
Supporting the integration and production of new data sources in a manner that minimizes development cycles while maximizing potential business applications
Building and maintaining relevant documentation and data dictionaries for the organization to ensure scalable knowledge

We look for teammates who have:

Bachelor/Master in a quantitative discipline (computer science, actuarial science, mathematics, statistics, economics, physics, engineering, or related field).
Experience with a modern (JSON-heavy) data warehouse and version control (e.g. Git)
Experience building and maintaining scalable data models, including relevant documentation and training
Experience with various business intelligence tools (Looker, Tableau, PowerBI)
Excellent communication skills and ability to translate messages depending on the stakeholder
Python + SQL need to have some projects using both
Attention to detail and curiosity related to data
Strong theoretical knowledge but pragmatic focus on action

Who you will work with:

Stanley Wang, Director, Pricing Analytics: Before joining Counterpart, Stanley worked as an actuary within the pricing solutions and methods team at USAA to combine actuarial pricing with data science models. Before that, he was a leading data scientist for Digital Partners, a Munich Re Company where he specialized in building data science models and insights for leading insurtech companies. He has had many other relevant roles such as capital modeling, risk management etc. He lives in New York with his growing family.
Tobias Schuler, Head of Data & Analytics Advisor: Tobias was previously the Head of Data and Analytics at Digital Partners, a Munich Re company. Tobias led a team that built out data integrations, business intelligence and advanced analytics across all insurtech partners spanning various P&C lines of businesses. Tobias is also a FCAS and has built systems to enable leading class insights for underwriting, actuarial, claims and finance experts while focusing on democratizing data. He enjoys traveling internationally and spending time with his 2 young daughters.
Chris Shafer, Special Projects: Chris is a published scientific author, having studied the neural correlates of gratitude at the lauded Brain and Creativity Institute. He has since helped to launch numerous businesses in which he held a variety of critical roles from product management to business operations to strategic partnerships. Chris received his bachelor’s degree in Biological Sciences from the University of Southern California.
Elizabeth Barsalou, Data Scientist: Before joining Counterpart, Elizabeth worked as a full stack data scientist in small business lending for Kabbage and BHG. She specialized in building data science models, infrastructure and strategies to extend credit to small businesses. She lives in San Francisco and spends her free time singing opera and playing with her dogs.

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