Backed by Index, Kleiner Perkins and NEA.
About the role
Own the dbt models and data marts that power Marketing analytics, activation, and reporting. Build, validate, and productionize predictive models (lead scoring, LTV, channel attribution, propensity) in partnership with Marketing and GTM stakeholders Found on 1752vc Careers, the job board for startup and VC roles.
What they're looking for
- Bachelor's degree in a quantitative field (CS, Statistics, Economics, Engineering, or equivalent experience)
- 5+ years of proven experience in analytics engineering, data science, or a closely adjacent function
- Advanced SQL and production-grade data modeling experience — dbt strongly preferred
- Python proficiency for modeling and analysis work
- Hands-on experience with a modern cloud warehouse (Databricks, Snowflake, BigQuery, or Redshift)
- Demonstrated experience shipping predictive models or applied ML in a business context
More about this role
We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Seattle, Washington D.C., Raleigh, London, and Amsterdam.
The Analytics Engineering team owns the full-stack analytics foundation for Plaid's GTM, CGX, NEA and Marketing organizations. We build and maintain the core semantic layer data models (dbt on Databricks), activation layer, and BI surfaces that these teams rely on — and we partner with stakeholders to turn those models into decisions, forecasts, analytics and experiments.
As a Senior Analytics...
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