Bestow Offices

Bestow is headquartered in Dallas.

Hybrid Workplace

Employees engage in a combination of remote and on-site work.

Bestow is a remote-first hybrid company; however, some roles will need to be connected to an office based on the job.

Typical time on-site: Flexible

U.S. Office Locations

HQ

Dallas

2700 Commerce Street Suite 1000, Dallas, TX, United States, 75226

Recently posted jobs

17 Hours AgoSaved
Remote or Hybrid
US
Big Data • Fintech • Information Technology • Insurance • Software
Owns accounting support for the deal desk and quote-to-cash process at a SaaS company. Responsibilities include reviewing contracts for ASC 606 implications, advising Sales and Legal on deal structures, establishing approval workflows, translating contract terms into billing configurations, managing amendments and renewals, and partnering with Sales Operations, Finance, and Accounting. The role also supports commercial governance, SaaS metrics analysis, audit, and cross-functional training.
YesterdaySaved
Remote or Hybrid
US
Big Data • Fintech • Information Technology • Insurance • Software
Own end-to-end product design for agent, wholesaler, and back-office insurance workflows. Conduct research, define problems, create user flows and Figma designs, build coded prototypes, validate solutions, and partner with engineering through implementation. Design integration experiences involving permissions, data imports, APIs, quoting, and status workflows. Contribute to design critiques and systems while balancing usability, trust, accuracy, compliance, technical constraints, and stakeholder needs in a regulated product environment.
6 Days AgoSaved
Remote or Hybrid
2 Locations
Big Data • Fintech • Information Technology • Insurance • Software
Build and productionize traditional machine learning models, owning feature engineering, validation, deployment, monitoring, drift detection, and retraining. Develop LLM-powered agentic tools, dashboards, self-serve analytics products, and automated insight pipelines. Partner with engineering and business stakeholders, write production-grade Python and SQL, drive adoption, improve data quality, and establish responsible AI workflows for a regulated industry.