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Applied Finance Jobs (NOW HIRING)

Hexion, Inc.

Senior Financial Analyst

Columbus, OH · On-site

$82K - $102K/yr

Applied Finance & Commercial Partnership * Apply your solutions to real financial problems - profitability analysis across products, customers, and regions; scenario planning; and forecasting that ...

Endex

Founding Designer

New York, NY · On-site

We're a team working on the frontier of agentic development and applied finance, in close collaboration with leading research labs and backed by OpenAI ($14M Raise in Aug. 2025). With significant ...

Endex

GTM

New York, NY · On-site

$125K - $156K/yr

We're a team working at the frontier of agentic development and applied finance, in close collaboration with leading research labs and backed by OpenAI ($14M raise in Aug. 2025). With significant ...

Applied Materials

M5 Senior Finance Manager

Santa Clara, CA · On-site

$158K - $218K/yr

Who We Are Applied Materials is a global leader in materials engineering solutions used to produce ... Job Summary This Senior Finance Manager leads a Corporate FP&A team with end-to-end ownership of ...

Endex

Recruiter

New York, NY · On-site

We're a team working on the frontier of agentic development and applied finance, in close collaboration with leading research labs and backed by OpenAI ($14M Raise in Aug. 2025). With significant ...

Endex

GTM Engineer

New York, NY · On-site

We're a team working on the frontier of agentic development and applied finance, in close collaboration with leading research labs and backed by OpenAI ($14M Raise in Aug. 2025). With significant ...

Endex

Operations

New York, NY · On-site

We're a team working on the frontier of agentic development and applied finance, in close collaboration with leading research labs and backed by OpenAI ($14M Raise in Aug. 2025). With significant ...

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All JobsApplied Finance Jobs

Applied Finance information

See salary details

$30.5K

$70.4K

$138K

How much do applied finance jobs pay per year?

As of Jun 29, 2026, the average yearly pay for applied finance in the United States is $70,370.00, according to ZipRecruiter salary data. Most workers in this role earn between $50,000.00 and $77,000.00 per year, depending on experience, location, and employer.

What is applied finance?

Applied finance is a field that focuses on using financial theory and quantitative methods to solve real-world problems in business, investing, and policymaking. It involves the practical application of concepts such as risk management, portfolio analysis, and financial modeling to help organizations make informed financial decisions. Professionals in applied finance work in areas like corporate finance, investment banking, asset management, and financial consulting. This discipline bridges the gap between theoretical finance and the practical needs of businesses and markets.

What do you learn in Applied Finance?

Applied Finance programs teach students about financial analysis, investment strategies, risk management, and financial modeling using tools like Excel and specialized software. The coursework often includes understanding financial markets, valuation techniques, and regulatory environments relevant to finance roles.

What can you do with a degree in Applied Finance?

A degree in Applied Finance prepares individuals for roles such as financial analyst, investment analyst, risk manager, or financial advisor. Graduates can work in banking, asset management, corporate finance, or financial consulting, often utilizing skills in financial modeling, data analysis, and using tools like Excel or financial software.

What can I do with an applied personal finance degree?

An applied personal finance degree prepares individuals for roles such as financial advisor, personal finance consultant, or financial planner. Graduates can work in banking, insurance, or investment firms, utilizing skills in budgeting, financial analysis, and client advising, often requiring certifications like CFP or CFA. The degree provides a foundation for careers focused on helping clients manage their finances and achieve financial goals.

What are the key skills and qualifications needed to thrive in Applied Finance, and why are they important?

To thrive in Applied Finance, you need strong analytical skills, a solid grounding in financial theory, and typically a degree in finance, economics, or a related field. Proficiency with financial modeling software, statistical analysis tools like Excel or Python, and familiarity with financial databases such as Bloomberg are commonly required. Excellent communication, problem-solving abilities, and attention to detail help professionals stand out in this role. These skills are crucial for making informed financial decisions, interpreting complex data, and clearly conveying insights to stakeholders in dynamic business environments.

What is the highest paying finance job?

In applied finance, chief financial officers (CFOs) and senior investment bankers typically earn the highest salaries, often exceeding several million dollars annually with bonuses and incentives. These roles require extensive experience, advanced degrees, and strong leadership skills, and they often involve overseeing company financial strategies or managing large investment portfolios.

What is the difference between Applied Finance vs Financial Analyst?

AspectApplied FinanceFinancial Analyst
Required CredentialsBachelor's degree in finance, economics, or related field; certifications like CFA beneficialBachelor's degree in finance, accounting, or economics; CFA often preferred
Work EnvironmentCorporate finance departments, investment firms, consultingBanking, investment firms, corporate finance teams
Industry UsageUsed across finance sectors for practical financial decision-makingCommonly used for analyzing financial data and advising investments

Applied Finance focuses on practical financial decision-making and problem-solving within organizations, often involving financial modeling and analysis. Financial Analysts primarily analyze financial data to guide investment and business decisions. While both roles require similar credentials and work environments, Applied Finance emphasizes applying financial principles directly to business strategies, whereas Financial Analysts focus on data analysis and reporting.

What are some common challenges faced by professionals in Applied Finance, and how can they be managed?

Professionals in Applied Finance often deal with rapidly changing market conditions, complex regulatory requirements, and the need to communicate technical financial concepts to non-financial stakeholders. Staying updated with industry trends and regulations is crucial, as is developing strong analytical and communication skills. Collaboration with cross-functional teams, such as accounting, risk management, and IT, is essential to provide comprehensive financial solutions and drive business objectives. Proactively seeking professional development opportunities and leveraging mentorship can also help overcome these challenges.
More about Applied Finance jobs
What states have the most Applied Finance jobs? States with the most job openings for Applied Finance jobs include:
What job categories do people searching Applied Finance jobs look for? The top searched job categories for Applied Finance jobs are:
Applied Finance jobs near you
Infographic showing various Applied Finance job openings in the United States as of June 2026, with employment types broken down into 83% Full Time, 15% Part Time, and 2% Contract. Highlights an 83% Physical, 6% Hybrid, and 11% Remote job distribution, with an average salary of $70,370 per year, or $33.8 per hour.

Sr Applied AI Engineer-Finance

Kion Group AG

Grand Rapids, MI • On-site

$113K - $174K/yr

Full-time

Posted 19 days ago

Job description

Dematic is standing up a Finance AI enablement team to drive adoption, build, and roll out AI and sophisticated analytics use cases across the global function.
As the Applied AI / Machine Learning Engineer, you will play a hands-on role crafting, developing, deploying, and operating AI and ML solutions tailored to Finance use cases such as financial planning, predictive analysis, irregularity identification, and management reporting.
This role is ideal for someone who can build production-ready models, translate business problems into AI solutions, and operate optimally in an environment that is early in its AI maturity with limited existing technical infrastructure.
The position will partner closely with Finance team members, IT (Dematic & parent co.), and other enterprise AI initiatives to ensure solutions are scalable, auditable, and aligned with standards.
We offer:
  • Career Development
  • Competitive Compensation and Benefits
  • Pay Transparency
  • Global Opportunities

Learn More Here: https://www.dematic.com/en-us/about/careers/what-we-offer
Dematic provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.
This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation and training.
The base pay range for this role is estimated to be $113,625 - $174,225 at the time of posting. Final compensation will be determined by various factors such as work location, education, experience, knowledge, and skills.
Tasks and Qualifications:
What you will do in this role:
AI / ML Solution Development
  • Design, develop, and deploy machine learning models and AI solutions tailored to Finance use cases (e.g., forecasting, planning, variance analysis, anomaly and risk detection).
  • Build and maintain ML models for financial planning, forecasting, trend analysis, and anomaly detection across large, structured datasets.
  • Develop LLM-powered tools to support financial analysis, commentary generation, summarization, and scripted insights for Finance users.
  • Translate Finance requirements into data pipelines, feature engineering, model architecture, and deployment approaches.

Model Validation & Governance
  • Conduct model validation, back-testing, and performance evaluation to ensure accuracy, robustness, and business relevance.
  • Evaluate model performance over time and diagnose issues related to data quality, concept drift, and changing business conditions.
  • Implement appropriate controls, explain-ability, and documentation to support Finance governance, audit, and compliance requirements.
  • Document model assumptions, methodologies, limitations, and change history for audit and risk review.

ML Ops & Deployment
  • Implement MLOps standard methodologies, including model versioning and lifecycle management, drift detection and performance monitoring, retraining schedules and automated pipelines, and reproducibility and rollback procedures.
  • Partner with IT to deploy models into enterprise environments (cloud, Salesforce, SAP, Snowflake, proprietary tools, etc.).
  • Ensure AI solutions are secure, scalable, and maintainable within enterprise standards.

Collaboration & Enablement
  • Collaborate with Finance, IT, data teams, and other AI workstreams to promote consistent standards, tooling, and patterns across the organization.
  • Serve as a technical thought partner to Finance leaders, helping shape the AI roadmap and identify high-value use cases.
  • Help educate Finance partners on AI capabilities, limitations, and responsible usage.
  • Contribute to establishing foundational AI practices for a growing Finance AI team.

What we are looking for:
  • Bachelor's degree in Computer Science, Data Science, Engineering, Applied Mathematics, Finance, or a related field.
  • 4-7+ years of proven experience in machine learning, data science, or applied AI with hands-on production deployment experience.
  • Strong experience building ML models using Python and common libraries (e.g., pandas, scikit-learn, PyTorch, TensorFlow).
  • Experience developing or integrating LLM-based solutions (prompt engineering, embeddings, retrieval-augmented generation, summarization).
  • Proven understanding of time-series forecasting, anomaly detection, regression, and classification techniques.
  • Experience with model validation, back-testing, performance monitoring, and explain-ability.
  • Practical experience implementing MLOps concepts (CI/CD for models, monitoring, version control).
  • Ability to work in a low-maturity AI environment, creating structure where little exists.
  • Strong communication skills with the ability to explain technical concepts to Finance and business audiences.

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