Onebrief is looking to improve its internal workflows and leverage data to drive insights across the organization by hiring a Data Science and Internal Tools Product Manager.
Requirements
- 4+ years building software products, with significant experience in data, analytics, internal tools, or platform products
- Strong technical fluency with data systems, SQL, and analytics tools—you should be comfortable exploring data and validating hypotheses independently
- Experience building internal tools or platforms that improved operational efficiency or enabled data-driven decision making
- Experience with experimentation frameworks, A/B testing, or statistical analysis
- Familiarity with data visualization tools (e.g., Tableau, Looker, or custom dashboards)
- Background in operations, business intelligence, or data engineering
Responsibilities
- Shape internal product initiatives: Define and scope projects that improve internal workflows, build data infrastructure, and enable data-driven decision making across the organization
- Drive data science initiatives: Partner with data scientists and engineers to translate business questions into analytical solutions, build experimentation frameworks, and develop tools that surface insights to stakeholders
- Build internal tools: Lead the development of tools that multiply force for our engineering, product, customer relations, sales, and operations teams—from deployment dashboards to workflow automation
- Enable cross-functional teams: Work closely with teams across Onebrief to understand pain points, prioritize high-impact initiatives, and ensure solutions are adopted and provide measurable value
- Establish data infrastructure: Define requirements for data pipelines, analytics platforms, and reporting systems that enable the company to operate with greater visibility and speed
Other
- The ideal candidate is a "product person" who knows how to build software products and understands the power of data.
- Someone who speaks the language of engineers, data scientists, and business stakeholders, and doesn't rely too heavily on them to devise and evaluate solutions.
- Someone who is intelligent, charismatic, ambitious, and intellectually honest enough to work with internal users and elicit non-obvious requirements.
- Someone who writes well and can communicate difficult concepts clearly and objectively to different audiences—from technical data scientists to non-technical operations teams.
- Finally, someone who is organized and naturally drives projects with the sense of ownership of a startup founder.
