Data Scientist

About the role

We believe communication belongs to everyone. We exist to democratize phone service.  TextNow is evolving the way the world connects, and that's because we're made up of people with curious minds who bring an optimistic yet critical lens into the work we do.   We're the largest provider of free phone service in the nation. And we're just getting started.

Join us in our mission to break down barriers to communication and free the flow of conversation for people everywhere.

About the role

We’re looking for a business-minded Data Scientist who pairs strong technical skills with sound judgment about which problems are worth solving. You’ll partner with product, marketing, finance, engineering, and trust & safety to turn ambiguous questions into rigorous analyses, models, and experiments — and then turn the results into decisions.

The problems are real and the data is large: understanding what drives user acquisition, engagement, and retention; improving monetization across ads and subscriptions; measuring the impact of product changes; and helping keep our network safe from fraud and abuse. You’ll own work end to end, from framing the question to landing the recommendation with leadership.

What you’ll do

- Frame the right questions. Work with stakeholders to understand business challenges, spot where data can make a difference, and translate open-ended questions into structured analyses with clear success criteria.

- Find what drives the business. Dig into large, complex datasets to uncover the trends, segments, and behaviors behind user growth, engagement, retention, and revenue.

- Build models that get used. Develop and apply statistical and machine learning methods — predictive models, segmentation, forecasting, causal inference — and evaluate them honestly, including their assumptions and limitations.

- Run and read experiments. Design, analyze, and interpret A/B tests and quasi-experiments that inform product and marketing decisions.

- Define how we measure success. Create meaningful metrics, KPIs, and dashboards that teams rely on to track performance and make trade-offs.

- Tell the story. Turn complex findings into clear, actionable recommendations for technical and non-technical audiences, including senior leadership.

- Raise the bar. Partner with data engineering on reliable data and tracking, build reusable analyses and tools, and help spread analytical best practices across the company.

What we’d like to see

- 4+ years of experience in data science, product or business analytics, or a related quantitative role, with a track record of analyses and models that changed decisions.

- Strong Python and SQL skills for data manipulation, analysis, and modelling on large datasets.

- A solid foundation in statistics, experimentation (A/B testing), and common machine learning techniques — and the judgment to choose the simplest approach that answers the question.