Director - Applied Analytics

Extraordinary opportunity. Exceptional experience. Sometimes in life, you find yourself in the right place, at the right time, looking at an opportunity so extraordinary it cannot be ignored. At Trucordia, our company is built on wildly successful businesses in our communities across the country, and now we’ve come together to create the next great insurance brokerage. We offer an unrivaled combination of people, tools and solutions, and deliver exceptional experiences and unmatched opportunities for our employees, clients and stakeholders. We celebrate both individual successes and collective accomplishments, making sure the industry recognizes the remarkable company we’re building together, as well as the impact we’re having on our clients and communities. Ranked as one of the fastest-growing companies in the U.S. for three consecutive years, we have more than 5,000 team members across 200 offices across the country, who actively, genuinely care about our clients, each other and the quality of our work, and in every interaction, represent a company that people want to work for and do business with. Trucordia Values We actively, genuinely CARE about our clients, each other and the quality of our work, and in every interaction, represent a company that people want to work for and do business with. We COLLABORATE continuously because, together, we are more powerful and make amazing things happen for our clients and company. We LEAD with intelligence, hunger, curiosity, energy and a future-focused attitude of “what’s next”? We are RESULT-ORIENTED , growth-focused and driven to out-perform expectations of what an insurance brokerage can achieve. We CELEBRATE both individual successes and collective accomplishments, making sure the industry recognizes the remarkable company we’re building together, as well as the impact we’re having on our clients and communities. 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. Most of it lives in different systems, in different shapes, and a lot of it we still go back to the carrier for. We're hiring a Senior Director of Applied Analytics to build the foundation that makes all of that data connected, trustworthy, and usable, including as the context layer underneath the AI we're building on top of it. 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 figure out what the data actually needs to do, then design and build it yourself. Sometimes that means pulling data in from carriers and other outside sources and organizing it once so nobody has to chase it again. Sometimes it means modeling and structuring what we already have so our systems and our AI have real context instead of guessing. 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. What You’ll Do:   Build the data foundation in three ways Consolidation. Bring in carrier data like claims information and commission statements, then organize and consolidate it once so our teams stop going back to the carrier for answers we should already have. 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. Sources of truth. Clean up and stand behind the systems the business runs on, starting with Dayforce, so access, reporting, producer numbers, and growth data all trace back to something we trust. This one starts on day one. 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. Organize the data underneath the AI. Structure, model, and govern the data that feeds our AI experiences so they have real context and know what to do instead of guessing. We want you working at the front edge of AI-first development, using AI tools to build faster and building data applications that go well beyond dashboards. Own it end to end. Take a solution from idea through architecture, modeling, testing, and into production on Snowflake and Azure. Work closely with Data Engineering. Set 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 the work in front of you into clear, sized proposals that leadership can actually prioritize and 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 data engineers, analytics engineers, and analysts, and set the bar for how they work. Leaders here stay in the work while they lead it, so expect to be a player-coach for the long run, not just the first year. 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. 10+ years in data engineering, data architecture, analytics, or similar roles, with a mix of hands-on building and leading people. You're a r