Data Analyst

The Company you’ll JoinAt 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 WithWe'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 DoDefine, report, and monitor key performance indicators of product areas, and lead deep dives into variations of critical metrics from normal behaviorUse Python and write SQL queries to improve data pipeline and generate reportsBuild data visualizations using Metabase and Jupyter notebooks as a method of conveying data insightsHelp engineering teams set up tests and perform statistical analysis of experimentsConvert analytical insights into concrete, meaningful recommendations for business or product improvement, and succinctly communicate these findings to various partners and leadershipAbout You5+ years experience in analytics, consumer-facing product experience preferredExperienced statistician with a track record of setting up and optimizing metrics tracking systems and A/B testing methodologiesExperience with building and maintaining data pipelines, ensuring data integrityProficient at both SQL and PythonA track record of leading cross-functional initiativesBonus points!Experience with DAG orchestrators (eg. Airflow)Consumer-facing product experienceOriginally posted on Himalayas