Director - Applied Analytics

Company Description: 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 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 building data foundations that other teams and systems now depend on: ingestion, modeling, consolidation, and cleanup work that held up over time.

Not just reports and dashboards.

setting data strategy, including spotting where data is missing and standing up new ways to collect it for specific goals.

building data applications and tools that put data in front of business users, and AI systems, in a way that actually gets used.

Real hands-on experience with Snowflake and the Microsoft Azure ecosystem, including pipeline and orchestration work with tools like Azure Data Factory, Azure Storage, and Azure ML or Databricks.

Strong data and analytics engineering skills: SQL, dimensional and semantic modeling, and Python or R.

You know what it takes to get data into production and keep it reliable once it's there.

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 especially care about structuring and grounding data so AI systems retrieve the right thing, and about using AI to build faster.

The ability to explain a data problem 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 Have: Experience in insurance, brokerage, financial services, or another regulated, data-heavy industry.

Familiarity with insurance data like policy, claims, submissions, commissions, and carrier or market data, and with agency management systems or an HRIS like Dayforce.

consolidating messy third-party data from outside partners, like carrier files, EDI feeds, or vendor statements. 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. What Success Looks Like: First 90 days : Get to know the data and the business priorities. With Data Engineering already in your corner, put together a ranked list of the foundation work that matters most, including where we'd need to start collecting new data, and have the Dayforce cleanup underway. 6 months : Ship at least one high-value solution into production yourself, proving the approach and setting the pattern for how analytics and engineering work together. 12 months : Point to a set of solutions with real, measurable impact, and use those results to start hiring and building out the team under you. Additional Information: Please see our company Benefits: Medical, Dental, Vision Life and AD&D insurance FSA / HSA Commuter & Child Care FSA Cancer Support Benefits Pet Insurance Accident & Critical Illness Hospital Indemnity Employee Assistance Program (EAP) 11 Paid Holidays Flexible PTO 401K Trucordia Insurance Services, LLC and its affiliates (collectively, the “Company”) is aware of scams involving false offers of employment with the Company. The false offers use fake websites, email addresses, group chats and text messages. The Company does not (a) interview prospective candidates via instant message or group chat; (b) request banking or credit card information during the interview process; or (c) require candidates to purchase products or services or process payments on its behalf as a condition of any employment offer. Trucordia is an equal opportunity employer. We believe that every employee has the right to work in an environment that is free from all forms of discrimination. It is our policy that all decisions involving any aspect of the employment relationship such as hiring, compensation and training, promotions, transfers, discipline, and termination will be based on merit, qualifications, and abilities. Such decisions will be made without regard to age, ancestry, color, race, national origin, disability, protected medical condition, genetic information, military service, veteran status, citizenship status, religion, creed, sex, gender, gender identity, sexual orientation, pregnancy, childbirth, marital status, or any other condition, characteristic or activity protected by law. Discrimination based on any of these factors is contrary to our operating philosophy. Attention Recruitment Agencies: Trucordia does not accept unsolicited resumes from any agencies that have not signed a mutual service agreement. All unsolicited resumes will be considered property of Trucordia, and we will not be obligated to pay a referral fee. This includes resumes submitted directly to hiring managers without contacting Trucordia's Talent Acquisition Department.