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About This Role
As a team member in Finance at Nationwide, a Fortune 100 company with nearly $70 billion in annual sales, the opportunities are endless! Let Nationwide help create your career journey! At Nationwide®, “on your side” goes beyond just words. Our customers are at the center of everything we do and we’re looking for associates who are passionate about delivering extraordinary care. This position is part of the AI Risk Governance team — a dedicated advisory function within Enterprise Risk Management.
- Provide technical depth to assess AI/ML and generative AI systems, and translate technical realities into clear risk language for both practitioners and risk partners.
- Advise first-line teams on risk management throughout the AI lifecycle, tailoring guidance to each use case's context rather than applying one-size-fits-all rules, so teams can contextualize AI risk and build fit-for-purpose mitigation strategies.
- Keep risk controls current with rapidly evolving AI technology (including agentic AI), anticipating emerging risks and updating guidance and control expectations ahead of scaled deployment.
- Serve as a trusted, credible advisor who connects and aligns risk partners across all three lines on AI risk matters.
- Support the operationalization of AI risk management through agentic AI — designing and building AI agents, automations, or purpose-built tooling that scale risk guidance and embed risk controls into practitioners' workflows.
- Contribute to shared legal and compliance support, assembling audit-ready evidence and helping produce credible, timely responses to regulator and examiner inquiries.
- Communicate complex technical and risk concepts in plain language, building practitioner fluency and confidence in managing AI risk through training and education.
Compensation Grade: G5
This role does not qualify for employer sponsored work authorization. Nationwide does not participate in the STEM OPT extension program.
It is our intention to fill this role in Columbus, OH. However, applications from candidates working remotely who bring critical industry skills and relevant experience may be considered.
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Job Description Summary
Do you have the desire to play a critical role in driving data-based business outcomes? At Nationwide, our Analytic professionals are responsible for modeling complex problems, discovering insights and identifying business opportunities using scientific research methods, statistics, machine learning and data visualization techniques. They participate in all phases of the analytic lifecycle, from research design, data collection and data processing to model building, deployment and presentation of results. Our industry-leading workforce adopts an agile work environment and a collaborative culture to deliver outstanding solutions and results. If that sounds like something you aspire to, we want to know more about you!
As an Analytic Solutions Advisor, you’ll be responsible for working with Nationwide business leaders and data scientists to design and implement advanced analytics solutions that deliver deep insights and translate into high business value to our organization. To succeed, you’ll need to use business knowledge and a solid understanding of advance analytics (e.g., artificial intelligence, machine learning, etc.) to prioritize business problems and convey goals to data science professionals. You’ll have the opportunity to work with various technologies from big data, relational and SQL databases, unstructured data technology and programming languages such as SQL and Python. Job Description
Key Responsibilities:
- Leads advanced analytics projects. Consults with business partners to define and structure analytic projects. Analyzes trends and patterns in structured and unstructured data and synthesizes and communicates relevant insights to project teams and business partners using advanced analytics techniques. May lead multiple concurrent projects.
- Builds, packages and communicates analytic work (synthesis) using appropriate medium for relevant insights and applicable data visualizations. Uses statistical techniques to determine patterns and predict future business outcomes and trends.
- Synthesizes project work and the work of team members. Work may span more than one project or focus area. Plans and manages execution of work, participates in planning, and delivers on commitments. Develops scope, risk/control matrix, project timelines and assignments.
- Collaborates with leadership to develop analytics strategies for the business unit. Consults with business to understand, align and deliver analytics work that supports business objectives and priorities.
- Designs analytics solutions aligned to business needs using statistical, database and/or general programming languages and tools.
- Reviews analytic solution design and provide relevant feedback and coaching to project team associates.
- Builds and manages relationships and serve as a trusted business advisor to clients, partners in Enterprise Analytics Office, Technology, Advanced Analytics Hubs, and other partners. . Builds partnerships across the enterprise to enhance analytics capabilities.
- Contributes to the continuous improvement of department processes through ongoing initiatives.
May perform other responsibilities as assigned.
Reporting Relationships: Reports to Manager/Director Data Leader.
Typical Skills and Experiences:
Education: Undergraduate studies in statistics, actuarial science, engineering or related quantitative field, business science or MBA preferred.
License/Certification/Designation: Certifications are not required but encouraged.
Experience: Typically, eight or more years of related work experience.
Knowledge, Abilities and Skills: Proven understanding of advanced analytics theory and experience with application in a key project and/or program. Strong verbal and written communication skills to interact with all levels of associates, senior management and vendors. Proficient in working with cross-functional teams to drive project execution.
Other criteria, including leadership skills, competencies and experiences may take precedence.
Staffing exceptions to the above must be approved by the hiring manager’s leader and HR Business Partner.
Values: Regularly and consistently demonstrates the Nationwide Values.
Job Conditions:
Overtime Eligibility: Exempt (Not Eligible)
Working Conditions: Normal office environment.
ADA: The above statements cover what are generally believed to be principal and essential functions of this job. Specific circumstances may allow or require some people assigned to the job to perform a somewhat different combination of duties.
We currently anticipate accepting applications until 10/11/2026. However, we encourage early submissions, as the posting may close sooner if a strong candidate slate is identified before the deadline. Benefits
We have an array of benefits to fit your needs, including: medical/dental/vision, life insurance, short and long term disability coverage, paid time off with newly hired associates receiving a minimum of 18 days paid time off each full calendar year pro-rated quarterly based on hire date, nine paid holidays, 8 hours of Lifetime paid time off, 8 hours of Unity Day paid time off, 401(k) with company match, company-paid pension plan, business casual attire, and more.
Nationwide is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive culture where everyone feels challenged, appreciated, respected and engaged. Nationwide prohibits discrimination and harassment and affords equal employment opportunities to employees and applicants without regard to any characteristic (or classification) protected by applicable law.
This position could be filled within any of the lower 48 U.S. states. Smoke-Free Iowa Statement: Nationwide Mutual Insurance Company, its affiliates and subsidiaries comply with the Iowa Smokefree Air Act. Smoking is prohibited in all enclosed areas on or around company premises as well as company issued vehicles. The company offers designated smoking areas in which smoking is permitted at each individual location. The Act prohibits retaliation for reporting complaints or violations. For more information on the Iowa Smokefree Air Act, individuals may contact the Smokefree Air Act Helpline at 888-944-2247.
For NY residents please review the following state law information: Notice of Employee Rights, Protections, and Obligations LS740 (ny.gov) https://dol.ny.gov/system/files/documents/2022/02/ls740_1.pdf NOTE TO EMPLOYMENT AGENCIES:
We value the partnerships we have built with our preferred vendors. Nationwide does not accept unsolicited resumes from employment agencies. All resumes submitted by employment agencies directly to any Nationwide employee or hiring manager in any form without a signed Nationwide Client Services Agreement on file and search engagement for that position will be deemed unsolicited in nature. No fee will be paid in the event the candidate is subsequently hired as a result of the referral or through other means.
Nationwide pays on a geographic-specific salary structure and placement within the actual starting salary range for this position will be determined by a number of factors including the skills, education, training, credentials and experience of the candidate; the scope, complexity and location of the role as well as the cost of labor in the market; and other conditions of employment. If a Sales job, Sales Incentives, based on performance goals are possible in addition to this range. Note on Compensation for Part-Time Roles: Please be aware that the salary ranges listed below reflect full-time compensation. Actual compensation may be prorated based on the number of hours worked relative to a full-time schedule. The national salary range for Consultant, Analytic Solution Advisor : $118,000.00-$222,000.00 The expected starting salary range for Consultant, Analytic Solution Advisor : $118,000.00 - $178,000.00
- Job Category Data & Advanced Analytics
- Position Type Full Time
- Posted 2026-10-06T07:15:53.747142+00:00
- Location(s) + Ohio - Columbus, One Nationwide Plaza + United States - Remote
- Line of Business
- Entity
- Recruiter
- Hiring Manager
- Experience Level
- Req ID 100573
Role Details
About This Role
AI/ML Engineers build and deploy machine learning models in production. They work across the full ML lifecycle: data pipelines, model training, evaluation, and serving infrastructure. The role has evolved significantly over the past two years. Where ML Engineers once spent most of their time on model architecture, the job now tilts heavily toward inference optimization, cost management, and integrating LLM capabilities into existing systems. Companies want engineers who can ship production systems, and the experimenter-only role is fading fast.
Day-to-day, you're writing training pipelines, debugging data quality issues, setting up evaluation frameworks, and figuring out why your model performs differently in staging than it did on your dev set. The best ML engineers are obsessive about reproducibility and measurement. They instrument everything. They know that a model is only as good as the data feeding it and the infrastructure serving it.
Across the 9,079 AI roles we're tracking, AI/ML Engineer positions make up 76% of the market. At Nationwide Mutual Insurance Company, this role fits into their broader AI and engineering organization.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
What the Work Looks Like
A typical week might include: debugging a data pipeline that's silently dropping 3% of training examples, running A/B tests on a new model version, writing documentation for a feature flag system that lets you roll back model deployments, and reviewing a junior engineer's PR for a new evaluation metric. Meetings tend to be cross-functional since ML touches product, engineering, and data teams.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
Skills Required
Python and PyTorch dominate the requirements. Most roles expect experience with cloud platforms (AWS, GCP, or Azure) and familiarity with ML frameworks like TensorFlow or JAX. RAG (Retrieval-Augmented Generation) has become a top-3 skill requirement as companies integrate LLMs into their products. Docker and Kubernetes show up in about a third of postings, reflecting the production focus of the role.
Beyond the core stack, employers increasingly want experience with experiment tracking tools (MLflow, Weights & Biases), feature stores, and vector databases. Fine-tuning experience is valuable but less common than you'd think from reading Twitter. Most production LLM work is RAG and prompt engineering, not fine-tuning. If you have both, you're in a strong position.
Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
Compensation Benchmarks
AI/ML Engineer roles pay a median of $211,950 based on 13,048 positions with disclosed compensation. Entry-level AI roles across all categories have a median of $111,000.
Across all AI roles, the market median is $213,000. Top-quartile compensation starts at $263,911. The 90th percentile reaches $318,400. For comparison, the highest-paying categories include AI Safety ($256,000) and Research Engineer ($252,000). By seniority level: Entry: $111,000; Mid: $193,200; Senior: $229,300; Director: $272,300; VP: $235,830.
Nationwide Mutual Insurance Company AI Hiring
Nationwide Mutual Insurance Company has 3 open AI roles right now. They're hiring across AI/ML Engineer. Based in Columbus, OH, US.
Location Context
Across all AI roles, 6% (531 positions) offer remote work, while 8,478 require on-site attendance. Top AI hiring metros: New York (3,078 roles, $221,000 median); San Francisco (2,646 roles, $261,000 median); Los Angeles (1,486 roles, $210,000 median).
Career Path
Common paths into AI/ML Engineer roles include Data Scientist, Software Engineer, Research Engineer.
From here, career progression typically leads toward ML Architect, AI Engineering Manager, Principal ML Engineer.
The fastest path into ML engineering is through software engineering with a self-directed ML education. A CS degree helps, but production engineering skills matter more than academic credentials. Build something that works, deploy it, and measure it. That portfolio project is worth more than a Coursera certificate. For career growth, the fork comes around the senior level: go deep on technical complexity (staff/principal track) or move into managing ML teams.
What to Expect in Interviews
Expect system design questions around ML pipelines: how you'd build a training pipeline for a specific use case, handle data drift, or design A/B testing infrastructure for model deployments. Coding rounds typically involve Python, with emphasis on data manipulation (pandas, numpy) and algorithm implementation. Take-home assignments often ask you to build an end-to-end ML pipeline from raw data to deployed model.
When evaluating opportunities: Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
AI Hiring Overview
The AI job market has 9,079 open positions tracked in our dataset. By seniority: 106 entry-level, 4,384 mid-level, 3,343 senior, and 1,246 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (531 positions). The remaining 8,478 roles require on-site or hybrid attendance.
The market median for AI roles is $213,000. Top-quartile compensation starts at $263,911. The 90th percentile reaches $318,400. Highest-paying categories: AI Safety ($256,000 median, 66 roles); Research Engineer ($252,000 median, 457 roles); AI Engineering Manager ($251,622 median, 55 roles).
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
The AI Job Market Today
The AI job market spans 9,079 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (6,862), AI Product Manager (453), AI Software Engineer (451). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (106) are outnumbered by mid-level (4,384) and senior (3,343) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 1,246 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (531 positions), with 8,478 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $213,000. Top-quartile roles start at $263,911, and the 90th percentile reaches $318,400. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $256,000 median, while Prompt Engineer roles sit at $141,440. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (1,649 postings), Aws (898 postings), Azure (723 postings), Rag (671 postings), Gcp (536 postings), Pytorch (434 postings), Claude (410 postings), Kubernetes (406 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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