Director - Applied Analytics

Trucordia•Lindon, UT

1d•Hybrid

About The Position

We're a large insurance brokerage, and we sit on a huge amount of data: policy, claims, submission, market, and client data across a lot of lines of business. We're hiring a Senior Director of Applied Analytics to help turn that data into real value for the business, whether that's new revenue streams, lower costs, or organic growth. This is a hands-on building role first, and a leadership role as it grows. Analytics and Data Engineering both report to the same leader, so you'll be working closely with the data engineering team from your first week. You'll partner with the business to find the opportunities worth chasing, then build and ship the solutions yourself. Sometimes that means turning data we already have into a product. Sometimes it means building better tools so the data we have is actually usable. And sometimes the data doesn't exist yet, so you'll figure out how to start collecting it. In every case, you take the idea all the way through to something running in production. Once you've proven a few wins, you'll hire and lead a team under you. We want someone who can move fast and build with their own hands now, and who can grow into running the function as the results earn it. The right person likes both parts of that: the building and the leading.

Requirements

10+ years in analytics, data science, or similar roles, with a mix of hands-on building and leading people.
You're a real builder who can also lead. You can design and ship a solution yourself, quickly, without waiting on a team, and you have the range to grow into leading one. If you only manage, or only build, this probably isn't the right fit. We need both.
A track record of using data to move more than one kind of number: revenue, cost, or growth. Not just reports and dashboards.
Experience setting data strategy, including spotting where data is missing and standing up new ways to collect it for specific goals.
Experience building data applications or products that put data in front of business users in a way they'll actually use.
Real hands-on experience with Snowflake and the Microsoft Azure ecosystem, including tools like Azure Data Factory, Azure Storage, and Azure ML or Databricks.
Strong analytics engineering skills: SQL, dimensional and semantic modeling, and Python or R. You know what it takes to get analytics into production.
General software and web development experience. You understand how modern applications are designed, built, and deployed, and you can build data applications, not just models and pipelines.
Hands-on experience with AI and machine learning, and a good read on where the field is going. We expect this person to be out front on AI-first development, using AI to build faster and building AI into the products they ship.
The ability to explain a data opportunity in plain business terms and defend a plan to senior leadership.
Comfort in ambiguity. You can find a path, and create one when it isn't there yet.

Nice To Haves

Experience in insurance, brokerage, financial services, or another regulated, data-heavy industry.
Familiarity with insurance data like policy, claims, submissions, and carrier or market data, and with agency management systems.
Experience building data products or analytics-as-a-service for clients.
A background in data governance, privacy, or compliance as it relates to how data gets used.
An MBA or an advanced degree in a quantitative field. Relevant, practical experience works just as well in place of a degree.

Responsibilities

Find and deliver value in three ways: Monetization (Turn our data into products that make money or save it, like benchmarking, packaged data products, or analytics we can offer internally or to clients and carriers), Operational efficiency (Use our data to make the business run better. Cut manual work, speed up processes, and give teams what they need to make faster, smarter calls), Organic growth (Build analytics that help us grow the business we already have, through cross-sell, better retention, higher win rates, and a stronger client experience).
Lead the building: Build where the data doesn't exist yet. For the initiatives that matter, figure out what data we'd need, then work with engineering and operations to set up a way to start capturing it, so today's gaps become tomorrow's assets.
Build data applications, AI-first. Create the apps and tools that make data genuinely usable, well beyond dashboards. We want you working at the front edge of AI-first development, using AI tools to build faster and putting AI capabilities into the products you ship.
Own it end to end. Take a solution from idea through modeling, testing, and into production on Snowflake and Azure.
Work closely with Data Engineering. Agree on shared standards for data models, pipelines, and how things get to production, so the work holds up and can be reused instead of rebuilt every time.
Set direction and grow the function: Make the case. Turn opportunities into clear, sized proposals that leadership can actually fund.
Build first, then build a team. Early on, you'll do the work yourself and prove it out. As the results justify it, you'll hire, mentor, and lead a team of analysts, data scientists, and analytics engineers, and set the bar for how they work.
Show the impact. Put real metrics on what your work is doing for the business, and report it to leadership.
Keep it responsible. Make sure everything you build respects data governance, client confidentiality, and the rules that come with insurance data, like usage rights and the handling of PII and PHI.