Attune is making it easier, faster, and more reliable for small businesses to access insurance! They all need insurance to protect their businesses, but when it comes time to get a policy, they're bogged down by hundreds of questions, lots of paperwork, and a seemingly never-ending timeline stretching for weeks or months.

We are changing all that. By using data and technology expertise to understand risk, automating legacy processes, and creating a better user experience for brokers, we're able to provide policies that are more applicable and more transparent in just minutes.

Simply put, we're pushing insurance into the future, focusing on accuracy, speed, and ease.

Our mission and our team are growing. In staying true to our values, we've earned our spot on many workplace award lists. Attune is dedicated to creating a diverse team of curious, focused, and motivated people who are excited about changing the future of an entire industry.

Position Overview:

As a Data Scientist at Attune, you'll work closely with stakeholders across Actuarial, Underwriting, Claims, Product, Revenue, and Customer Experience. You'll develop predictive models, test hypotheses, explore new data sources, and integrate your findings into the tools and workflows that power our business. You'll also contribute to improving our internal data infrastructure, ETLs, and dashboards.

What You'll Do:

Partner with teams across the business—from Underwriting to Customer Experience—to understand their goals and identify how data can drive better decisions. You'll translate business needs into analytical approaches and communicate findings in a clear, actionable way.
Analyze customer and broker behavior to improve engagement, retention, and conversion. This includes segmentation, churn analysis, usage patterns, and anomaly detection to flag unusual or risky behavior.
Investigate business problems and test hypotheses using rigorous data exploration. Examples might include: What types of risks are associated with higher loss ratios? How do product usage patterns correlate with retention? Where can we find operational efficiencies?
Develop predictive models and statistical analyses to support pricing, reserving, underwriting, and claims initiatives. You'll apply a mix of statistical and machine learning techniques (e.g., regression, classification, clustering) to solve complex business problems with real-world impact.
Explore new internal and third-party datasets, evaluate their usefulness, and incorporate them into models and dashboards to unlock new insights or increase model performance.
Operationalize your work by integrating models into tools and workflows used by other departments. Collaborate with engineering and product to ensure insights are accessible, scalable, and reliable.
Contribute to the improvement of our internal data infrastructure, including helping to maintain and enhance ETLs, develop internal data tools or APIs, and optimize our reporting and dashboarding ecosystem.
Support ad-hoc data requests and deep dives, helping teams get quick answers to pressing questions and identifying longer-term opportunities for automation or model development.

What We're Looking For:

5+ years of experience in a data science, analytics, or statistics-focused role
Excited about working with business leads across many different functions to solve real day-to-day problems using data
Hands-on experience with predictive modeling, including regression, classification, clustering, and other ML techniques
Familiarity with advanced statistical modeling (Bayesian modeling, hierarchical models, etc.) is a plus Proficiency in Python and SQL
Bonus: Familiarity with P&C insurance data and industry-specific modeling challenges

What We Offer: