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How much do phd in finance jobs pay per hour?

As of Aug 7, 2026, the average hourly pay for phd in finance in Missouri is $19.13, according to ZipRecruiter salary data. Most workers in this role earn between $16.01 and $21.44 per hour, depending on experience, location, and employer.

What types of career paths are available to someone with a PhD in Finance?

A PhD in Finance opens doors to a variety of career paths, including academia, research roles in think tanks, quantitative analysis positions in financial institutions, and policy advisory roles in government agencies. Many graduates pursue tenure-track professorships, where they balance teaching with conducting original research. Others join investment banks, hedge funds, or consulting firms, leveraging their advanced analytical skills to solve complex financial problems. The role often involves collaboration with professionals from economics, statistics, and data science, offering a dynamic and intellectually stimulating work environment.

What are the key skills and qualifications needed to thrive as a PhD in Finance?

To thrive as a PhD in Finance, you need advanced quantitative analysis skills, deep knowledge of financial theory, and a strong academic background, typically with a doctorate in finance or a related field. Expertise in statistical software (such as Stata, R, or Python), econometric modeling, and familiarity with academic publishing standards are essential. Strong critical thinking, presentation abilities, and collaboration skills help you communicate complex research and work effectively with peers. These competencies are crucial for producing impactful research, teaching effectively, and contributing to both academic and industry advancements.

What is a PhD in Finance?

A PhD in Finance is a doctoral degree focused on advanced research in financial theory, markets, and quantitative methods. It prepares graduates for careers in academia, research institutions, and high-level industry positions, such as quantitative analysts or policy advisors. The program typically involves coursework in economics, econometrics, and finance, followed by original research culminating in a dissertation. Students develop strong analytical, mathematical, and research skills, making them experts in their field.

Is it hard to get a PhD in finance?

A PhD in finance is a challenging academic program that requires strong quantitative skills, research ability, and dedication over several years. It involves rigorous coursework, comprehensive exams, and original research, making it a demanding but rewarding path for those interested in academic or research careers in finance.

Is it worth getting a PhD in finance?

A PhD in finance prepares individuals for academic, research, and high-level analytical roles in finance, often requiring strong quantitative skills and familiarity with statistical tools. It can lead to careers in university teaching, research institutions, or specialized industry positions, but it typically involves several years of study and limited immediate job opportunities compared to other finance degrees.

What can I do with a PhD in finance?

A PhD in finance prepares individuals for careers in academia, research, and high-level analytical roles in finance firms, consulting, or government agencies. Graduates often work as university professors, financial analysts, quantitative researchers, or policy advisors, utilizing advanced statistical, mathematical, and economic skills. The degree also enables roles that require deep expertise in financial modeling, risk management, and data analysis.
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Phd In Finance jobs near you
Infographic showing various Phd In Finance job openings in Missouri as of July 2026, with employment types broken down into 78% Full Time, 6% Part Time, and 16% Contract. Highlights an 74% Physical, 4% Hybrid, and 22% Remote job distribution, with an average salary of $39,797 per year, or $19.1 per hour.

Staff Software Engineer, DevProd AI

Jobtailor

California, MO • On-site

$180 - $240/hr

Other

Posted 2 days ago

New

Job description

  • Partner with internal and external stakeholders to re-envision and scale Core Engineering technologies, including the design and build of a suite of AI Agents
  • Drive technical excellence and governance of AI Agents as use-cases are identified across Snap Engineering
  • Collaborate across teams to understand product requirements, evaluate architectural trade-offs, and deliver solutions needed to build innovative products and services
  • Champion best practices in availability, scalability, operational excellence, and cost management
  • Serve as a technical mentor to senior engineers and a thought partner to engineering leaders
  • Contribute to the technical roadmap for AI Agents and Core SWE infrastructure, ensuring alignment with organizational goals
  • Partner closely with Product, Finance, Sales, and Engineering teams distributed across multiple offices
  • Influence key architectural and implementation decisions for scalable, reliable, and cost-effective engineering solutions
  • Iterate quickly without compromising quality and continuously raise the bar on operational excellence
  • Adapt technical plans nimbly in response to evolving customer and business needs
Requirements
  • Bachelor's Degree in a relevant technical field such as computer science or equivalent years of practical work experience
  • 9+ years of post-Bachelor’s software development experience; or a Master’s degree in a technical field + 8+ year of post-grad software development experience; or a PhD in a related technical field + 5+ years of post-grad software development experience
  • Experience as a technical lead, domain expert or owner of complex technical initiatives
  • Experience building large scale storage, backend or distributed systems
Core Competencies

Demonstrates expertise in AI Agent development and large-scale system architecture, with a strong focus on operational excellence, scalability, and cost management. Proven ability to mentor technical teams and influence architectural decisions in alignment with organizational goals.

Highest-signal resume keywords
  • AI Agent Development
  • Large Scale Storage Systems
  • Technical Leadership
  • Software Development Experience
  • Architectural Decision-Making
ATS Optimization KeywordsHard Skills
  • Software Development
  • Distributed Systems
  • Backend Development
  • Technical Roadmap Contribution
  • Operational Excellence
Soft Skills
  • Collaboration
  • Mentoring
  • Influencing Stakeholders
  • Adaptability
Certifications & Qualifications
  • Bachelor's Degree in Computer Science
  • Master's Degree in Technical Field
  • PhD in Related Technical Field
Industry Keywords
  • Core Engineering Technologies
  • Scalability
  • Cost Management
  • Governance
  • Product Requirements
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