Credit Quant Analyst - AI-Driven Investment Analytics Remote

Nationwide Mutual Insurance Company

Columbus (OH)

Hybrid

USD 127,000 - 213,000

Full time

14 days+

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Benefits offered by this job

401(k) match

Pension plan

Paid time off

Job summary

Nationwide is seeking an experienced Investment Professional - Quantitative Analyst to translate complex investment questions into scalable analytics across fixed income, multi-asset, and other portfolios. You will build tools, dashboards, and models that drive asset allocation, portfolio construction, and trading decisions with AI-enabled processes and a governance-first mindset.

You will partner with PMs, analysts, and front-office colleagues to deliver repeatable insights, robust monitoring,

Qualifications

Bachelor's degree in finance/economics/math/stats/engineering/cs; advanced degree or CFA preferred.
Eight+ years of investment or quantitative experience supporting portfolio management, research, trading, or analytics.
Experience applying AI/ML or AI-assisted workflow techniques to investment research in a governed environment.
Strong grounding in portfolio analytics, statistics, econometrics, and quantitative research methods.
Proficiency in Python and/or R; familiarity with Databricks.

Responsibilities

Partner with Portfolio Managers and analysts to shape and test investment ideas by building and maintaining analytic views, signals, and tools that help source and prioritize opportunities.
Support security selection and trade design through fair-value, relative-value, scenario, and contribution analysis across relevant asset classes and portfolios.
Enhance sizing, portfolio construction, and ongoing monitoring by developing views, optimization frameworks, dashboards, and standard analytics packs that help investment teams evaluate diversification, concentration, and performance versus expectations.
Conduct quantitative research on portfolio construction, asset allocation, and strategy questions, and package outputs into reusable decision-support tools rather than one-off analysis.
Leverage the analytics/semantic layer and approved AI tools to make research, monitoring, and reporting faster, more consistent, and easier to reuse across teams and books.
Collaborate with enterprise portfolio managers and front office teams to show how strategies and positions contribute to broader portfolio positioning and objectives.
Build reusable research, monitoring, and portfolio analytics capabilities that can be embedded into recurring investment workflows, rather than producing only one-time analysis.
Use approved AI-enabled tools where appropriate to accelerate research, signal generation, scenario design, monitoring, and reporting while maintaining transparency, human judgment, and clear documentation of assumptions and limitations.
Partner with Data, Technology, and front office teams to move high-value analytics and model outputs from prototype work into stable, repeatable decision-support workflows.
Contribute to an evolving research culture that values simple, usable, explainable models first, with iteration over time as business needs, data quality, and platform capabilities improve.
Help define data requirements, validation checks, and monitoring standards for models, signals, and decision-support tools used across portfolios and asset classes.
Support the development of shared analytics standards, research templates, and reusable model components that improve consistency across teams.
May perform other responsibilities as assigned.