The Sr. Actuarial Analyst, ADP will be a member of the Enterprise Risk Management (ERM) team for their first rotation. They will assist the Fortitude Re Actuarial team in performing Valuation, Financial Reporting, Modeling, Experience Studies, Assumptions, Capital Management, Inforce Management and/or Pricing activities. This candidate will participate in the Actuarial Development Program (ADP) which provides support in passing actuarial exams.

This role will be based in our Nashville, TN office on a hybrid basis.

What You Will Do:

• Periodic US GAAP, Statutory, and Tax valuations.
• Analysis and preparation of financial results.
• Building, maintenance and execution of models.
• Coding and testing of programs, processes and models.
• Ensuring that all work aligns with the Fortitude Re Control Framework.
• Technical reviews of work done by other teams or colleagues.
• Process improvement efforts and automation.
• Responding to internal and external auditor requests.
• Ad hoc project work.
• Analysis of hedging strategy and ALM strategy development, in coordination with risk management and the investments hedging team.
• Continue to pass actuarial exams and modules to maintain status in the Fortitude Re ADP to earn your Associateship or Fellowship.

What You Will Have:

• A Bachelor’s degree in Actuarial Science, Mathematics, Statistics, Economics, or a related field, and:
  • Passed at least 4 actuarial exams.
  • 1.5 years of experience minimum.
• Strong proficiency in Excel; proficiency with Python and/or Julia is preferred.
• Experience with actuarial software (AXIS) is a plus; familiarity with SQL, Power BI, or other data analytics tools will be very useful.
• Ability to assist on multiple work assignments and meet time commitments.
• Ability to work well both independently and with others.
• Highly motivated, inquisitive and results oriented.
• The desire and ability to deliver accurate and completed work products.
• Strong oral and written communication skills.

#LI-Hybrid

About the Role

We are building a differentiated advisory practice at the intersection of AI strategy, governance, and security. As organizations move from AI experimentation to enterprise-scale deployment, they face urgent questions: How do we govern AI responsibly? How do we secure agentic architectures? How do we align technical capabilities with business strategy and regulatory requirements?

This role is designed for a technically grounded early-career professional who wants to help answer those questions alongside senior practitioners. You will work directly with the practice lead on client-facing engagements, contribute to the development of proprietary frameworks and tools, and build expertise in one of the fastest-growing areas of consulting.

This is not a traditional strategy consulting role, and it is not a pure engineering role. It sits at the intersection—you need to be comfortable reading Python, understanding how LLMs and agentic systems work, AND translating that knowledge into governance frameworks, risk assessments, and executive-ready deliverables. If you thrive at the border between technical depth and business impact, this is for you.

What You Will Do

Client Delivery (50–60%)

• Support the design and delivery of AI governance assessments for clients across industries, leveraging frameworks such as ISO/IEC 42001, NIST AI RMF, and the EU AI Act.
• Conduct technical reviews of client AI systems, architectures, and deployments to identify governance gaps, security vulnerabilities, and risk exposure.
• Develop AI risk registers, control mappings, and maturity assessments tailored to each client’s organizational context and regulatory landscape.
• Prepare client-facing deliverables including assessment reports, executive briefings, implementation roadmaps, and policy recommendations.
• Participate in workshops and stakeholder interviews with client teams ranging from data scientists to C-suite executives.

Practice Development (25–30%)

• Help build and refine the practice’s proprietary AI governance and security framework, integrating industry standards with practical implementation experience.
• Research emerging AI risks, including those specific to agentic AI systems, LLM-based applications, MCP architectures, and AI supply chains.
• Develop reusable tools, templates, and accelerators (e.g., assessment questionnaires, control libraries, risk scoring models) to scale the practice.
• Contribute to thought leadership content: draft LinkedIn posts, white papers, blog articles, and conference presentation materials.
• Monitor regulatory and standards developments (EU AI Act, state-level AI legislation, ISO/IEC updates, OWASP LLM Top 10) and maintain a current knowledge base.

Technical Contribution (15–20%)

• Build proof-of-concept tools and demos using Python to illustrate governance and security concepts for clients (e.g., prompt injection demonstrations, model evaluation dashboards, automated compliance checks).
• Evaluate and test AI platforms, tools, and vendor solutions from a governance and security perspective.
• Support the practice lead’s technical fluency development by preparing technical briefings, annotated code walkthroughs, and “translation” materials that bridge technical and executive audiences.
• Stay hands-on with AI/ML development trends: experiment with agentic frameworks (LangChain, LangGraph, CrewAI), RAG architectures, and model evaluation techniques.

What We Are Looking For

Required Qualifications

• 2–3 years of professional experience in one or more of the following areas: AI/ML engineering, data science, or cybersecurity.
• Bachelor’s degree in Computer Science, Data Science, Information Systems, Cybersecurity, Engineering, or a related field. Master’s degree is a plus but not required.
• Working proficiency in Python and comfort navigating data science tooling (Jupyter, Pandas, Scikit-learn, or equivalent).
• Foundational understanding of machine learning concepts: supervised/unsupervised learning, model training and evaluation, overfitting, bias-variance tradeoff.
• Familiarity with LLM-based applications: understanding of how large language models work (at minimum: tokenization, embeddings, attention, fine-tuning vs. RAG vs. prompt engineering).
• Strong written and verbal communication skills—you must be able to explain technical concepts to non-technical stakeholders clearly and concisely.
• Comfort working in ambiguity: this is a practice being built, not a mature team with fully defined processes. You need to be self-directed and resourceful.

Preferred Qualifications

• Exposure to AI governance or risk management frameworks (ISO/IEC 42001, NIST AI RMF, EU AI Act, OWASP LLM Top 10, MITRE ATLAS).
• Experience with agentic AI frameworks (LangChain, LangGraph, CrewAI, AutoGen) or understanding of agent architectures and tool-use patterns.
• Understanding of MCP (Model Context Protocol) or similar protocols for AI system integration and the security implications thereof.
• Background in cybersecurity, including familiarity with security frameworks (NIST CSF, ISO 27001) and how they intersect with AI-specific risks.
• Experience in a consulting or professional services environment, including client-facing work and deliverable development.
• Relevant certifications such as: CISA, CISSP, CCSP, AWS/Azure AI certifications, or ISO 42001 Lead Implementer/Auditor.
• Bilingual English/Spanish is a strong plus.

The Kind of Person Who Thrives in This Role

We are not looking for someone who fits neatly into a single box. The ideal candidate is a “bridger”—someone who can move fluidly between a technical deep dive and an executive conversation. Specifically:

• You’re a builder, not just an analyst. When you see a gap in a process or a tool, your instinct is to prototype something—a script, a template, a dashboard, not just write a slide about it.
• You’re curious about “why” and “so what.” You don’t just want to understand how a transformer model works; you want to understand what that means for how organizations should govern and secure it.
• You write well. A significant portion of this role involves producing written work—reports, frameworks, articles—and clarity of writing is non-negotiable.
• You’re comfortable being the least experienced person in the room. You’ll be in meetings with CIOs, CISOs, and senior partners. You need the confidence to contribute and the humility to learn.

What We Offer

• Accelerated growth trajectory: You’ll be building a practice from the ground up alongside senior leadership, gaining exposure and responsibility that would take years to earn in a larger, more established team.
• Investment in your learning: Budget for certifications, training programs, and conference attendance.
• Client diversity: Work across industries and with organizations at different stages of AI maturity—from Fortune 500 companies to mid-market firms navigating their first AI initiatives.

About Truework

Truework, recently acquired by Checkr, provides access to crucial employment and income information needed for mortgage loans, apartment rentals, background checks, and more. We’re disrupting a $5B+ industry dominated by legacy incumbents and outdated processes. Within Checkr, Truework operates independently, allowing rapid iteration while leveraging the strengths and assets of the core business.

About the Role

This role sits on Checkr’s Operations Insights & Analytics team, directly supporting Truework’s operations team as its primary analytics partner. Truework’s operations are more complex than a typical help desk — and deeply understanding their processes will be central to your success in this role.

Truework already has some operations reporting and data infrastructure in place, but as the first dedicated analyst focused on this work, you’ll own the process of improving and expanding it. Some existing dashboards need to be rebuilt or consolidated, sources-of-truth established, and the team needs reliable performance & cost metrics. You’ll also contribute to the near-term migration from Looker to Omni Analytics.

The ideal candidate is someone who can context-switch between hands-on data work and strategic analysis, thrives in ambiguity, and is energized by making messy things clean. You should be someone who, when given a high-level goal, figures out what questions to ask, what data is needed, and what infrastructure would provide it — and then builds it.

What You’ll Do

Drive Analysis & Business Performance

• Build and maintain models for cost, headcount, and operational performance that inform leadership decisions across Truework operations
• Track and analyze team performance week-over-week, identifying trends, bottlenecks, and opportunities for efficiency gains
• Translate technical findings into clear recommendations for stakeholders at all levels, from operational teams to executive leadership

Build & Improve Reporting

• Define and standardize key operational metrics, working with stakeholders to ensure shared understanding of definitions and methodology
• Consolidate and rebuild existing dashboards, validating data accuracy and filling gaps in coverage
• Build production dashboards and self-service reporting in Omni Analytics, giving Truework’s operations teams reliable visibility into team performance

Strengthen Data Infrastructure

• Improve and expand existing data models to support reliable analytics across Truework’s operations
• Write and maintain dbt models, manage data pipelines, and work with raw database schemas to strengthen analytical foundations
• Identify and fix data quality issues — bad joins, missing records, misaligned definitions — before they become reporting problems
• Contribute hands-on to migrating Truework’s data infrastructure onto Checkr’s systems, working independently to navigate unknowns and solve technical problems as they arise

What You Bring

Required

• 5+ years of experience in analytics, data engineering, or a hybrid role — ideally in a high-growth or startup environment where you’ve had to build things from scratch
• Advanced SQL: complex joins, window functions, CTEs, query optimization. You should be able to navigate unfamiliar database schemas and figure out how data fits together.
• Hands-on experience with data modeling and pipeline tools (dbt, Airflow, or similar). You’ve built and maintained data models, not just queried them.
• Strong BI experience building production dashboards (Looker, Tableau, or similar). You know how to design reporting that’s actually useful, not just comprehensive.
• Comfort working in ambiguous environments with incomplete information. You don’t wait for perfectly defined requirements — you figure out what’s needed and start building.
• Strong communication skills: you can explain technical concepts to non-technical stakeholders and advocate for data quality and infrastructure investments
• An A-player mindset with a strong bias for action: you raise the bar, move with urgency, stay resilient through ambiguity, and take ownership to deliver meaningful outcomes.

Preferred

• Python for data manipulation, scripting, and statistical analysis
• Experience with data migration projects — moving data between systems, reconciling schemas, validating parity
• Domain experience in operations analytics, fintech, or verification/identity services
• Familiarity with version control (Git) and software engineering practices in an analytics context

What You Get

• A fast-paced and collaborative environment
• Learning and development allowance
• Competitive compensation and opportunity for advancement
• 100% medical, dental, and vision coverage
• Up to $25K reimbursement for fertility, adoption, and parental planning services
• Unlimited PTO policy
• Monthly wellness stipend