The role

As a member of the analytics team your mandate is to bring clarity to vast amounts of internal and external data so we can make better data driven business decisions, faster. You’ll do so by building high-quality and scalable ground truth data sets and performing analysis that delivers actionable insights for the business. This role is focused on Customer Operations, spanning front and back office functions, automation capabilities, and agent staffing. Your work will cover data models, data tests, data infrastructure and BI tools.

This role is responsible for:

• Partnering with data engineering, operations, analytics and other stakeholder teams to build data solutions for complex data requirements via data models, queries and dashboards

• Managing our data observability and testing strategy to ensure strong coverage and high data quality

• Establishing syntactic, performance, and testing standards for analytical models that can be deployed at scale

• Developing business expertise and proactively identifying areas of improvement for data insights

• Creating reports and dashboards that effectively communicate insights and recommendations to key stakeholders in a clear and concise manner

You bring

• 5+ years of analytics engineering experience; consumer financial companies preferred

• Customer operations analytics experience is a bonus: servicing, disputes, fraud, automation, etc.

• Strong proficiency with SQL and Python

• Expertise working with enterprise data warehousing solutions, like Databricks, Snowflake, and BigQuery. We use Databricks

• Professional experience using using a SQL-based transformation solution, preferably dbt (Data Build Tool), to build complex and performant analytical models 

• Experience designing and implementing architectural models that address data movement across multiple systems and handling of associated dependencies

• Proven ability to translate data into compelling visualizations with BI tools (Looker, Databricks dashboarding)

• Proven ability to work cross-functionally to translate complex data models into practical business guidance

• Proven ability to work independently to solve complex and at times ill-defined problems

• Proven ability to communicate clearly to technical and non-technical audiences

• Intellectual curiosity to look beyond the ‘what’ and answer the ‘why’

• An act-like-an-owner mentality. We have a bias toward taking action.