Staff Applied Data Scientist: AI/ML for Risk & Vision (Austin)

Steadily; Austin (TX); On-site; USD 140,000 - 190,000; Full time

Benefits offered by this job

Free snacks

Team lunches

Collaborative office culture

401(k)

Medical, dental, vision insurance

HSA

Job summary

Steadily seeks a Staff Applied Data Scientist in Austin to own building, evaluating, and deploying ML models across our data-rich product ecosystem. You will work with image data, scale models to production, and monitor quality to prevent regressions in a fast-growing, ambiguous environment.

The role is in-office in Austin, TX on our Engineering team, reporting to leadership and partnering with product and operations to drive business impact.

Qualifications

• 5+ years experience applying data science methods to production problems.
• Past experience as a team lead is a plus.
• Product-focused with ability to translate data insights into value.
• Comfort working in ambiguous environments and autonomous.
• Strong curiosity about business drivers.

Responsibilities

• Design, build and evolve data sets and models with scalability, quality and maintainability.
• Own and lead exploration and implementation of new areas of science in our product ecosystem.
• Write clean, maintainable Python/R code, with high quality.
• Partner with Engineering, Product, Operations and Business teams to design reliable solutions.
• Provide metrics and visibility into model quality, bias and performance.

Skills

Production ML

Team leadership

Python

Model evaluation

Image analysis

Tools

Python

R

Pytorch

TensorFlow

Airflow

Job description

Steadily seeks a Staff Applied Data Scientist in Austin to own building, evaluating, and deploying ML models across our data-rich product ecosystem. You will work with image data, scale models to production, and monitor quality to prevent regressions in a fast-growing, ambiguous environment.

The role is in-office in Austin, TX on our Engineering team, reporting to leadership and partnering with product and operations to drive business impact.