Staff Applied Data Scientist

Reposted 6 Days Ago
Be an Early Applicant
Austin, TX, USA
In-Office
180K-360K Annually
Senior level
Insurance
The Role
Lead design, build, and deployment of scalable ML/AI models (including image/vision) to production. Collaborate with engineering and business teams, monitor model quality and bias, and apply data-driven solutions to predict and aggregate risk.
Summary Generated by Built In

Location: Austin, TX

Employment Type: Full-time, In-Office

Department: Engineering

Compensation: Top of market salary + equity

As a Staff Applied Data Scientist:

You will play a key technical role on our Engineering team, identifying and evaluating trends, insights across large data sets and where having more refined data or internal ML/AI models could improve our product outcomes or operations. You’ll own building, evaluating, and deploying these models to production and monitor for quality and accuracy over time to prevent regressions and ensure continued relevance. We operate across data types including public, proprietary and a large volume of image data. You’ll operate with a high degree of autonomy and serve as a trusted technical owner for business problems across the organization. Steadily is still early in our exploration and application of where AI/ML models can drive the biggest business value, so this role is ideal for Scientists who like operating in ambiguous environments and to explore where the most impactful focus and methods should be applied.

This is a full-time, in-office position based in Austin, TX

Job Responsibilities
  • Design, build and evolve data sets and models with an emphasis on scalability, quality and maintainability, identifying the appropriate technique and approach to meet the needs of the business. Focus areas could be estimating risk at the property level, how to accurately assess property costs and using aerial image analysis or modelling techniques to identify individual attributes that feed into other models.

  • Own and lead exploration and implementation of new areas of science application in our product ecosystem to better predict risk both on a per-insured level and in aggregate across the entire portfolio.

  • Write clean, maintainable R/Python code, setting a high bar for quality and adherence to best practices.

  • Partner closely with Engineering, Product, Operations and Business teams to design reliable solutions across systems.

  • Provide excellent metrics and visibility into model quality, bias and performance to assess how it’s helping the business ensure a high bar of scientific rigor and evaluation.

What we’re looking for:
  • Experienced: 5+ years experience applying Data Science methods to production problems. We expect you to be able to dive into a complex codebase without too much spin-up. Past experience as a team lead is definitely a plus.

  • Builder: You like the product-side of data and think about how to apply modeling and evaluation techniques to real-world problems. You have thoughtful opinions about where the data leads and how to maximize the business impact of your work.

  • Pragmatic: We prioritize impact and delivery. You balance speed and quality, making thoughtful trade-offs to solve problems effectively. You leverage off-the-shelf solutions so we don’t re-invent the wheel but understand when a custom solution is appropriate.

  • Curious: you are not just an order-taker... you are curious about what makes the business tick and you learn the intricacies of how it runs. This results in strong intuition for when analysis is wrong and leads you to suggest ideas and insights that nobody thought to ask for. You’re not the type of scientist who wants fully fleshed-out specs thrown over the wall for you to implement.

Nice to have:

  • Actuarial experience, or experience applying models to risk evaluation and aggregation problems.

  • Experience in vision photo analysis

Additional Information:
  • Applicants must be authorized to work in the United States. We are unable to provide visa sponsorship at this time.

What We Offer:
  • Compensation: Top of market salary + equity

  • Time Off: 3 weeks PTO + 6 federal holidays

  • Insurance: Medical, dental, vision, life, disability, HSA, FSA

  • Retirement: 401(k)

  • Perks: Free snacks, team lunches, collaborative office culture

Why Join Steadily:
  • Good company. Our founders have three successful startups under their belt and have recruited a stellar team to match.

  • Top compensation. We pay at the top of the Austin market (see comp).

  • Growth opportunity: We’re an early-stage, fast-growing company where you’ll wear a lot of hats and shape product decisions.

  • Strong backing. We’re growing fast, we manage over $20 billion in risk, and we’re exceptionally well-funded.

  • Culture: Steadily boasts a very unique culture that our teammates love. We call it like we see it and we’re nothing if not candid. Plus, we love to have a good time. Check out our culture deck to learn what we’re all about.

  • Awards: We've been recognized both locally and nationally as a top place to work. Recently we were ranked 16th on Forbes' 2026 Best Startup Employers list, and 63rd on the prestigious Inc 5000 Fastest Growing Companies list. We've also been recognized as one of the Best Landlord Insurance Companies in 2026 by CNBC, a Top 2025 Startup in Newsweek, in Investopedia's Best Landlord Insurance Companies, and we won Austin Business Journal's Best Places to Work in 2025.

We’re excited to meet you!

Skills Required

  • 5+ years applying data science methods to production problems
  • Experience building, evaluating, and deploying ML models to production
  • Ability to write clean, maintainable R/Python code
  • Authorized to work in the United States (no visa sponsorship)
  • Past experience as a team lead
  • Actuarial experience or experience applying models to risk evaluation and aggregation
  • Experience in vision/photo analysis or aerial image analysis

Steadily Insurance Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Steadily Insurance and has not been reviewed or approved by Steadily Insurance.

  • Fair & Transparent Compensation Pay is considered strong and positioned as top‑of‑market, with explicit messaging about benchmarking to beat competing offers. Candidates can opt to trade some salary for equity, signaling a clear pay philosophy and choice.
  • Equity Value & Accessibility Equity grants are commonly included and highlighted across roles, and new hires can exchange salary for additional options. This positions ownership as a meaningful part of total rewards.
  • Career-Linked Recognition & Rewards High performers in sales and some customer-facing roles can achieve strong total earnings through base plus commission and performance upside. Role descriptions emphasize substantial on‑target earnings potential to align rewards with results.

Steadily Insurance Insights

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The Company
Austin, Texas
136 Employees
Year Founded: 2020

What We Do

We built Steadily to serve landlords who want their insurance to work like other modern tools they love: fast and affordable with excellent service. We're headquartered in Austin, Texas where we combine our decades of insurance experience with strong tech and design to delight our customers

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