Applied Data Scientist — Equity & Risk Modeling (Austin)

Steadily Insurance Agency; Austin (TX); On-site; USD 130,000 - 180,000; Full time

Benefits offered by this job

Equity

PTO 3 weeks

6 public holidays

Health insurance

401(k)

Free snacks

Collaborative culture

Job summary

Steadily Insurance Agency is hiring for an onsite data scientist in Austin, TX. You will design, build and deploy machine learning models to predict risk, collaborating with Engineering, Product, Operations and Business teams with a high degree of autonomy.

The role requires 5+ years applying data science to production problems, a builder mindset, and a pragmatic approach to balance speed and quality. Technologies include Python and R, with strong collaboration across the org.

Qualifications

• 5+ years of experience applying data science methods to production problems.
• Prior team leadership experience is a plus.
• Builder mindset: you focus on the product side of data.
• Pragmatic approach: balance speed and quality, reuse off the shelf solutions when appropriate.
• Curious and business-minded: understand business operations and propose new ideas.

Responsibilities

• Design and evolve data sets and models with a focus on scalability, quality and maintainability.
• Contribute to property level risk estimation and modeling to derive attributes for other models.
• Lead exploration and implementation of new scientific applications to improve risk prediction.
• Write clean, maintainable code in Python and R, upholding quality standards.
• Collaborate with Engineering, Product, Operations and Business teams to design cross-system solutions.
• Provide clear metrics on model quality, bias and performance for evaluation and business impact.

Skills

Data science

Leadership

Business mindset

Production problems

Tools

Python

R

Job description

Steadily Insurance Agency is hiring for an onsite data scientist in Austin, TX. You will design, build and deploy machine learning models to predict risk, collaborating with Engineering, Product, Operations and Business teams with a high degree of autonomy.

The role requires 5+ years applying data science to production problems, a builder mindset, and a pragmatic approach to balance speed and quality. Technologies include Python and R, with strong collaboration across the org.