Data Analyst
The Company you’ll Join
At Truv, our mission is to make verifications easy for everyone.
We think it’s crazy that it can take 5 to 7 days to verify someone’s employment or income. Alternatives are even worse, an API call should not cost $40.
When Truv succeeds, we'll save billions of dollars for companies and billions of hours for people who're still filling out forms and uploading paystubs.
Imagine applying for a loan or verifying your job history with a click of a button. That's what Truv is empowering.
The Team You’ll Work With
We're a small but mighty team of engineers, product managers, and business folks who built and launched products at Apple, Uber, Facebook, Carta, Venmo, Telegram, and Plaid. We're well funded by US-based top VC funds.
We like to nerd out about using the cutting-edge tech and building frictionless user experiences. We love crafting great products and see our users delighted by what we build.
We're a distributed team with no plans to start an office anytime soon. We don't really care where you are, but we care a lot about who you are. If you like solving customer pain points, helping your team members excel at what they do, being part of a community, and care about quality, you'll fit in.
Define, report, and monitor key performance indicators of product areas, and lead deep dives into variations of critical metrics from normal behavior
Use Python and write SQL queries to improve data pipeline and generate reports
Build data visualizations using Metabase and Jupyter notebooks as a method of conveying data insights
Help engineering teams set up tests and perform statistical analysis of experiments
Convert analytical insights into concrete, meaningful recommendations for business or product improvement, and succinctly communicate these findings to various partners and leadership
5+ years experience in analytics, consumer-facing product experience preferred
Experienced statistician with a track record of setting up and optimizing metrics tracking systems and A/B testing methodologies
Experience with building and maintaining data pipelines, ensuring data integrity
Proficient at both SQL and Python
A track record of leading cross-functional initiatives
Experience with DAG orchestrators (eg. Airflow)
Consumer-facing product experience
