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.
What You’ll Do
- 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
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