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Explainable Ai Jobs in Ohio (NOW HIRING)

Lead Data Scientist

Columbus, OH · On-site

$100 - $130/hr

... AI innovation into actionable business insights. This position plays a critical role in pricing ... Ensure models are scalable, performant, explainable, and maintainable in production environments.

... AI innovation into actionable business insights. This position plays a critical role in pricing ... Ensure models are scalable, performant, explainable, and maintainable in production environments

... AI innovation into actionable business insights. This position plays a critical role in pricing ... Ensure models are scalable, performant, explainable, and maintainable in production environments

Showing results 41-48

Explainable Ai information

What is the difference between Explainable Ai vs Data Scientist?

AspectExplainable AiData Scientist
CredentialsTypically requires knowledge of AI, machine learning, and data analysis; certifications like AI or ML courses are commonRequires degrees in computer science, statistics, or related fields; certifications in data analysis or machine learning are beneficial
Work EnvironmentWorks within AI development teams, focusing on model transparency and interpretabilityWorks across data analysis, model building, and business insights, often in research or corporate settings
Industry UsageUsed in AI development, healthcare, finance, and any field requiring transparent AI modelsApplied in tech, finance, healthcare, and research for data-driven decision making

Explainable Ai focuses on making AI models transparent and understandable, ensuring trust and compliance. Data Scientists develop and analyze models, often working with complex data. While both roles involve AI and data, Explainable Ai specialists emphasize interpretability, whereas Data Scientists focus on model creation and insights.

What are some of the typical challenges faced when working in Explainable AI and how do professionals address them?

Professionals in Explainable AI often encounter challenges such as balancing model accuracy with interpretability, translating complex model outputs into understandable insights for non-technical stakeholders, and ensuring transparency without compromising sensitive data. Addressing these issues typically involves using specialized tools and frameworks for visualization, collaborating closely with data scientists, domain experts, and business teams, and staying updated on the latest research in model interpretability. Continuous learning and open communication are key to overcoming these challenges and delivering AI solutions that are both effective and trustworthy.

What are the key skills and qualifications needed to thrive as an Explainable AI specialist?

To thrive as an Explainable AI specialist, you need a strong background in machine learning, data science, and statistics, typically with an advanced degree in computer science or a related field. Familiarity with frameworks such as TensorFlow, PyTorch, and libraries like LIME or SHAP, as well as experience in model interpretability tools, is essential. Strong analytical thinking, effective communication, and the ability to translate complex technical concepts for non-technical stakeholders are crucial soft skills. These capabilities ensure that AI models are transparent, trustworthy, and can be responsibly integrated into decision-making processes.

What is Explainable AI?

Explainable AI (XAI) refers to methods and techniques in artificial intelligence that make the results of AI models understandable and interpretable by humans. XAI aims to provide transparency into how AI systems make decisions, helping users trust and effectively manage AI applications. This is especially important in fields like healthcare, finance, and law, where understanding the reasoning behind AI-driven outcomes can be crucial for accountability and compliance. By making AI more transparent, XAI also helps identify and address biases or errors in AI systems.
What are popular job titles related to Explainable Ai jobs in Ohio? For Explainable Ai jobs in Ohio, the most frequently searched job titles are:
What cities in Ohio are hiring for Explainable Ai jobs? Cities in Ohio with the most Explainable Ai job openings:
Infographic showing various Explainable Ai job openings in Ohio as of August 2026, with employment types broken down into 48% Full Time, and 52% Contract. Highlights an 82% In-person, and 18% Remote job distribution.

Senior Data Analyst, Investment Professional

Nationwide Mutual Insurance Company

Columbus, OH • On-site

$127 - $213/hr

Other

Medical, Dental, Vision, Life, Retirement, PTO

Posted 10 days ago


Job description

## Senior Data Analyst, Investment ProfessionalApplylocations: Ohio - Columbus, One Nationwide Plazatime type: Full timeposted on: Posted 2 Days Agojob requisition id: 099377As 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.The hired associate must reside within 35 miles of the following location:Columbus: One Nationwide Plaza, Columbus OH, 43215Work schedule: 3 days in office, 2 days remote.This role does not qualify for employer sponsored work authorization. Nationwide does not participate in the STEM OPT extension program.#LI-SS1**Job Description Summary**Do you thrive on making sense of complex data and transforming it into insight that drives business impact? Are you energized by working at the crossroads of analytics, technology, and investment strategy? If solving challenging data problems in a highly collaborative, mission-driven environment excites you, this is the job for you. As a Consultant, Investment Professional Data Analyst, you will play a critical role in shaping how Nationwide Investments leverages data to deliver smarter, faster, and more consistent decisions. You’ll build the analytic structures and reusable data products that power front-office dashboards, AI-driven workflows, and quantitative tools. You’ll apply your technical expertise and collaborate with your team to design high-impact solutions that matter in a multi-billion-dollar investment portfolio environment.******Job Description******* Design curated analytic data structures and shared business logic, including sectors, ratings, strategy tags, benchmarks, and other core dimensions, in partnership with Data Governance and Data Management.* Provide controlled, reusable data access through SQL, APIs, and related interfaces for quantitative analysts, portfolio manager, enterprise portfolio managers, reporting teams, enabling a consistent source of truth for investment analytics.* Build and maintain the analytics and semantic layer that supports front-office dashboards, quantitative tools, and research workflows.* Monitor and improve the quality, consistency, and documentation of analytical data and reports that sit on top of enterprise golden sources.* Support data needs for AI and agentic workflows in a governed, auditable way, including input/output structuring and data persistence.* Collaborate with Technology and platform teams to align the analytics layer with enterprise architecture, including Snowflake, Databricks, and Aladdin.* Support continuous improvement of data, tooling, and reporting processes across the investment analytics function.* Build analytics-ready datasets and reusable data products for reporting, research, quantitative models, and evolving AI-enabled workflows, rather than one-off extracts or bespoke data pulls.* Apply automation and AI-enabled techniques where appropriate to improve data ingestion, tagging, reconciliation, anomaly detection, metadata capture, and documentation, with human review and appropriate controls.* Help improve coding, testing, version-control, and documentation practices for the production of data pipelines, analytical datasets, and related workflow tools.* Design data assets and interfaces that are explainable, documented, and reusable across front office teams, while reducing manual spreadsheet-based processing and redundant logic.* Support the evolution of the investment analytics architecture by ensuring data structures, mappings, and lineage are compatible with changing enterprise platforms, workflows, and future-state needs.* Contribute to a collaborative team environment that emphasizes experimentation, shared tooling, documentation, and continuous improvement across data and analytics processes.May perform other responsibilities as assigned.**Reporting Relationships:** Reports to leader of Investment Analytics. This is an individual contributor role.**Typical Skills and Experiences:****Education: Bachelor’s** degree in computer science, information systems, data analytics, mathematics, engineering, or a related field preferred. Advanced degree or relevant certifications preferred.**Experience:** Typically, eight or more years’ experience building and supporting analytical data, business intelligence, or investment data environments. Experience working with enterprise data warehouses, analytical reporting, and reusable data models in a complex business setting is preferred. Experience in financial services, asset management, insurance, or capital markets is desirable. Experience supporting AI-enabled analytics, analytics engineering workflows, or governed automation in an enterprise environment is preferred.**Knowledge, Abilities and Skills:**Proven advanced SQL and data-modeling capability with experience building complex queries and robust analytical data models. Hands-on experience with Snowflake and comfort working in modern analytics environments such as Databricks. Practical Python skills for data engineering and analytics (pandas, PySpark, or similar). Demonstrated experience designing and maintaining analytics or semantic layers for BI and quantitative use cases. Experience publishing reusable datasets to BI tools such as Power BI/Tableau, including dataset design and performance tuning. Working familiarity with investment data structures such as positions, transactions, benchmarks, and reference data. Understanding of data governance, lineage, quality monitoring, and version control practices. Ability to work cross-functionally and communicate technical concepts clearly. Familiarity with automation or AI-enabled data workflow techniques with human oversight. Knowledge of software engineering practices relevant to analytics environments, including Git, pull requests, and documentation. Ability to balance speed, control, transparency, and maintainability. Curiosity and comfort in tech-evolving team environments.Staffing exceptions to the above must be approved by the hiring manager’s leader and HR Business Partner.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 Human Resource Business Partner.**Values:** Regularly and consistently demonstrates Nationwide Values.**Job Conditions:**Overtime Eligibility: ExemptWorking Conditions: Normal office environment.Values: Regularly and consistently demonstrates Nationwide Values.ADA: The above statements cover what are generally believed to be the 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.**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. To learn more about the benefits we offer, click here.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. **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 Investment Professional - Data Analyst : $127,000.00-$213,000.00The expected starting salary range for Investment Professional - Data Analyst : $127,000.00-$213,000.00 #J-18808-Ljbffr