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Financial Engineer Jobs (NOW HIRING)

Dematic

Sr Applied AI Engineer-Finance

Grand Rapids, MI · On-site

The Applied AI / Machine Learning Engineer will develop and deploy AI solutions for various finance ... financial planning, forecasting, trend analysis, and anomaly detection across large, structured ...

Tidal Vision

FP&A Water-Engineer

Bellingham, WA · On-site

$115K - $130K/yr

JOB TITLE: FP&A Water-Engineer DEPARTMENT:CESCO SOLUTIONS REPORTS TO:BUSINESS MANAGER STATUS:EXEMPT/SALARY LOCATION:PACIFIC NORTHWEST (HYBRID/FLEXIBLE) SALARY: $115,000-$130,000/year based on ...

Kiongroup

Sr Applied AI Engineer-Finance

Grand Rapids, MI · On-site

$113K - $174K/yr

As the Applied AI / Machine Learning Engineer, you will play a handson role crafting, developing ... Build and maintain ML models for financial planning, forecasting, trend analysis, and anomaly ...

Kiongroup

Sr Applied AI Engineer-Finance

Atlanta, GA · On-site

$113K - $174K/yr

As the Applied AI / Machine Learning Engineer, you will play a handson role crafting, developing ... Build and maintain ML models for financial planning, forecasting, trend analysis, and anomaly ...

Ironclad

Finance Systems & AI Engineer

San Francisco, CA · On-site

$130K - $163K/yr

Own FP&A planning platform end-to-end: model architecture, formula logic, dimension hierarchies ... FP&A Engineering at a high-growth technology company, with demonstrated ownership of outcomes ...

New

Slate Auto

Finance Analytics & AI Engineer

Business performance dashboard consolidating company-wide financial and operational KPIs for ... data engineering, and AI. This person will be foundational in building Slate's next-generation ...

Rightway

Analytics Engineer

New York, NY

$140K/yr

ABOUT THE ROLE: We're hiring an Analytics Engineer to help design and build a PBM Financial Risk Engine that brings together claims, contract terms, pricing and utilization data to support financial ...

Rightway

Analytics Engineer

New York, NY · On-site +1

$140K/yr

ABOUT THE ROLE: We're hiring an Analytics Engineer to help design and build a PBM Financial Risk Engine that brings together claims, contract terms, pricing and utilization data to support financial ...

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Financial Engineer information

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$76K

$110.8K

$136K

How much do financial engineer jobs pay per year?

As of Jun 27, 2026, the average yearly pay for financial engineer in the United States is $110,812.00, according to ZipRecruiter salary data. Most workers in this role earn between $100,000.00 and $124,500.00 per year, depending on experience, location, and employer.

What is the difference between Financial Engineer vs Quantitative Analyst?

AspectFinancial EngineerQuantitative Analyst
Required CredentialsDegree in finance, mathematics, or engineering; often CFA or FRM certificationsDegree in finance, mathematics, or statistics; often CFA or FRM certifications
Work EnvironmentFinancial institutions, hedge funds, investment banksAsset management firms, hedge funds, investment banks
Job FocusDeveloping complex financial models, derivatives pricing, risk managementData analysis, model development, trading strategies
Common UsageDesigning financial products and strategiesAnalyzing data to inform trading decisions

Financial Engineers and Quantitative Analysts share similar educational backgrounds and certifications, often working in similar environments like investment banks and hedge funds. While Financial Engineers focus on creating complex financial models and derivatives, Quantitative Analysts primarily analyze data to support trading strategies. Both roles require strong quantitative skills and contribute to financial innovation and risk management.

What Engineers make $500,000?

Senior financial engineers, quantitative analysts, and risk managers in finance often earn $500,000 or more annually, especially with bonuses and profit-sharing. These roles typically require advanced skills in mathematics, programming, and financial modeling, along with extensive experience and often professional certifications like CFA or FRM.

What Engineers make $300,000 a year?

Senior financial engineers, especially those working in quantitative finance, hedge funds, or investment banks, can earn $300,000 or more annually through base salary, bonuses, and profit sharing. High-level roles often require advanced skills in mathematics, programming, and financial modeling, along with extensive experience and sometimes professional certifications like CFA or FRM.

What are some common challenges Financial Engineers face when developing quantitative models, and how can they address them?

Financial Engineers often encounter challenges such as ensuring model accuracy, dealing with incomplete or noisy data, and adapting models to rapidly changing market conditions. Addressing these issues typically requires strong collaboration with data scientists, risk managers, and traders to validate assumptions and stress-test models under various scenarios. Staying current with industry trends and regulatory requirements also helps Financial Engineers maintain robust, compliant solutions that add value to their organizations.

What are the key skills and qualifications needed to thrive as a Financial Engineer, and why are they important?

To thrive as a Financial Engineer, you need a strong background in mathematics, statistics, finance, and programming, typically supported by a degree in quantitative fields such as finance, mathematics, engineering, or computer science. Familiarity with technical tools like Python, R, MATLAB, financial modeling software, and sometimes certifications like CFA or FRM is highly valued. Exceptional problem-solving, analytical thinking, and the ability to communicate complex concepts clearly are vital soft skills. These skills and qualifications are crucial for designing innovative financial models, managing risks, and enabling data-driven decision-making in complex financial environments.

Do Goldman Sachs hire Engineers?

Goldman Sachs hires engineers, including financial engineers, software engineers, and quantitative analysts, to develop trading algorithms, risk models, and financial software. Candidates typically need strong technical skills, programming experience, and relevant finance knowledge. The firm offers roles in technology and finance departments with competitive hiring standards.

What is the work of a financial engineer?

A financial engineer develops mathematical models and uses quantitative techniques to analyze and manage financial risks, design financial products, and optimize investment strategies. They often work with programming tools like Python or R and require strong skills in mathematics, finance, and computer science. Their work supports trading, risk management, and financial decision-making in financial institutions.

What Is a Financial Engineer?

A financial engineer, also called a computational engineer, advises clients on investment strategies and risk management based on quantitative analysis of their portfolio and the atmosphere in the stock market. As a financial engineer, your job duties include analyzing the stock market to predict how stocks will perform, building models of trends in the stock market based on market history, and make recommendations on how to manage their portfolio.

What is a Financial Engineer?

A Financial Engineer is a professional who applies mathematical techniques, computational tools, and financial theory to solve complex problems in finance. They are often involved in designing financial products, developing risk management strategies, and building quantitative models for pricing, trading, and portfolio management. Financial Engineers typically work for banks, investment firms, or financial technology companies, and their expertise is essential for managing financial risks and innovating new financial instruments.
More about Financial Engineer jobs
What cities are hiring for Financial Engineer jobs? Cities with the most Financial Engineer job openings:
What are the most commonly searched types of Financial Engineer jobs? The most popular types of Financial Engineer jobs are:
Who are the top companies hiring for Financial Engineer jobs? The top employers for Financial Engineer jobs are:
What states have the most Financial Engineer jobs? States with the most job openings for Financial Engineer jobs include:
What job categories do people searching Financial Engineer jobs look for? The top searched job categories for Financial Engineer jobs are:
What are popular job titles related to Financial Engineer jobs? For Financial Engineer jobs, the most frequently searched job titles are:
Financial Engineer jobs near you
Infographic showing various Financial Engineer job openings in the United States as of June 2026, with employment types broken down into 99% Full Time, and 1% Contract. Highlights an 89% Physical, 3% Hybrid, and 8% Remote job distribution, with an average salary of $110,812 per year, or $53.3 per hour.
Sr Applied AI Engineer-Finance

Sr Applied AI Engineer-Finance

Dematic

Grand Rapids, MI • On-site

Full-time

Posted 15 days ago

Dematic rating

8.0

Company rating: 8.0 out of 10

Based on 16 frontline employees who took The Breakroom Quiz

142nd of 419 rated machine equipment manufacturers

Job description

Job Summary:
Dematic is establishing a Finance AI enablement team to enhance the adoption and implementation of AI and sophisticated analytics in their global finance function. The Applied AI / Machine Learning Engineer will develop and deploy AI solutions for various finance use cases, ensuring they are scalable and aligned with enterprise standards.
Responsibilities:
• 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.
• 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.
• 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.
• 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.
Qualifications:
Required:
• 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.
Company:
The Mind Behind the Machine Dematic is a trusted partner in intelligent automation for the supply chain, helping organizations design, build, and evolve solutions that perform in the real world. Founded in 1819, the company is headquartered in Atlanta, Georgia, US, , with a team of 10001+ employees. The company is currently Late Stage.

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