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Investment Banking Python Jobs (NOW HIRING)

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Investment Banking Python information

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How much do investment banking python jobs pay per hour?

As of Jun 4, 2026, the average hourly pay for investment banking python in the United States is $58.62, according to ZipRecruiter salary data. Most workers in this role earn between $48.32 and $66.59 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an Investment Banking Python Developer, and why are they important?

To thrive as an Investment Banking Python Developer, you need strong programming skills in Python, a solid understanding of financial products, and a relevant degree in computer science or finance. Familiarity with databases (such as SQL), financial modeling tools, and version control systems (like Git) is typically required, along with experience in financial software libraries. Excellent problem-solving, attention to detail, and effective communication are vital soft skills in this role. These skills are crucial for building robust financial systems that support critical trading and risk management operations in the fast-paced investment banking environment.

How does Python programming contribute to day-to-day tasks in an investment banking role?

In investment banking, Python is widely used to automate data analysis, build financial models, and streamline reporting processes. Professionals in this role frequently collaborate with traders, analysts, and risk managers to develop tools that enhance decision-making and operational efficiency. Mastery of Python enables team members to quickly prototype solutions, manipulate large datasets, and integrate with financial platforms. This not only increases productivity but also opens up opportunities for involvement in complex projects such as algorithmic trading and quantitative research.

What is Investment Banking Python?

Investment Banking Python refers to the use of the Python programming language within investment banking roles. Professionals in this area use Python for tasks such as financial modeling, data analysis, automating repetitive processes, risk management, and building trading algorithms. Python's simplicity and extensive libraries make it a popular choice for handling large datasets and complex calculations in banking. As the finance industry increasingly relies on technology, Python skills are highly valued in investment banking.

What is the difference between Investment Banking Python vs Quantitative Analyst?

AspectInvestment Banking PythonQuantitative Analyst
Required CredentialsBachelor's in Finance, Economics, or related; Python skillsDegree in Mathematics, Statistics, or Finance; Python proficiency
Work EnvironmentFinancial firms, investment banks, client-facingHedge funds, asset management, research teams
Industry UsageData analysis, automation, financial modelingModel development, risk analysis, algorithmic trading

Investment Banking Python professionals focus on automating financial models and data analysis within investment banks, often working closely with traders and analysts. Quantitative Analysts develop complex models for trading strategies and risk management, typically in hedge funds or asset management firms. While both roles require Python skills and a quantitative background, their work environments and primary objectives differ, with Investment Banking Python roles centered on supporting banking operations and Quantitative Analysts on trading and investment strategies.

AI Business Engineer - Investment Banking Experience

Raymondjames

Raleigh, NC

$65K - $140K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 11 days ago


Job description

Job Description Summary

The AI Business Engineer supports the adoption and effective use of generative AI across the Investment Bank and Capital Markets & Advisory functions by designing, building, and improving AI-powered solutions across banker workflows through custom GPTs and prompts and emerging agent-based tools. This role blends technical curiosity with practical application and deep business knowledge, contributing to prompt engineering, solution development, and user support while maintaining best practices and documentation. The individual partners with stakeholders to deliver training, troubleshoot issues, and enhance user experience, while also evaluating technology trends and vendors to drive innovation and business value.

Job Description

Responsibilities

  • This role will directly support the Investment Bank and Capital Markets & Advisory function and its use of generative AI, including GPTs and future agent-based solutions.
  • Support the design, development, testing, and ongoing improvement of GPTs, AI-powered workflows, and (over time) agent-based solutions
  • Assist with prompt engineering, prompt optimization, and documentation of effective prompting patterns and use cases
  • Help maintain standards, best practices, and internal documentation related to AI tools, automation, and innovation platforms
  • Provide hands-on support to internal users, helping troubleshoot issues and improve overall user experience with AI-enabled tools
  • Design and deliver role-specific training to finance professionals
  • Contribute to short- and long-term innovation roadmaps through research, analysis, and execution support
  • Analyze technology trends, tools, and vendor offerings to identify opportunities for experimentation or business value
  • Generate insights and recommendations that help improve internal technology offerings and identify areas for growth
  • Assist with data analysis and reporting related to innovation initiatives, pilots, and outcomes
  • Create and maintain presentation materials, including PowerPoint decks, charts, and visuals for leadership and stakeholder updates
  • Facilitate meetings with internal teams and external vendors; capture notes, actions, and follow-ups
  • Draft concise summaries, reports, or briefing materials on technology topics, vendors, or pilot results
  • Contribute ideas and perspectives to brainstorming sessions and innovation ideation efforts

Skills

  • The ideal candidate is curious, technically inclined, and excited about applying emerging technologies-especially generative AI-to real business problems.
  • 1-4 years of experience in technology, software, digital innovation, or related roles (financial services experience a plus, but not required)
  • Strong interest in generative AI, automation, and modern software platforms (e.g., LLMs, GPTs, agents, APIs, low-code/no-code tools)
  • Working knowledge of Python and SQL to support data exploration, workflow automation, and AI prototype development; ability to read, modify, and apply scripts with guidance from engineering partners - deep software engineering experience not required
  • Proficiency in data analysis using advanced Excel (e.g., pivot tables, XLOOKUP/VLOOKUP, conditional logic) to support reporting, pilot measurement, and business case development
  • Experience supporting or managing vendors, including coordination around licenses, contracts, or service delivery
  • Working knowledge of project and program management fundamentals
  • Ability to operate effectively in a fast-paced, evolving environment and adapt quickly as priorities and technologies change
  • Demonstrated ability to think creatively and encourage new approaches or ways of working
  • Strong written communication skills, with the ability to explain technical or complex concepts clearly and concisely
  • Comfortable creating and interpreting charts, diagrams, tables, and other data visualizations
  • Genuine interest in following technology trends, innovation research, and emerging tools
  • Excellent verbal communication and collaboration skills
  • High attention to detail with the ability to manage multiple workstreams simultaneously
  • Team-oriented mindset with the ability to work across technical and non-technical stakeholders

What success looks like

  • High-value AI use cases are moved from idea to pilot to scaled adoption.
  • Solutions are deployed with clear testing, documentation, and governance controls.
  • Banker adoption increases and workflows show measurable improvement in speed, quality, or user experience.
  • The team develops reusable assets and a repeatable operating model rather than one-off prompts.

Education

Bachelor's degree in computer science, engineering, information systems, data science, finance, economics, or a related field, or equivalent practical experience.

Work Experience

General Experience - 1 to 6 years

Education

Bachelor's (Required)

Work Experience

General Experience - 3 to 6 years

Certifications

Salary Range

$65,000.00-$140,000.00

Travel

Less than 25%

Workstyle

Hybrid

The total compensation for this position includes base salary or wages, and may include components such as additional compensation (cash or equity), discretionary bonuses, or commissions. This position is eligible for a benefits package that may include medical, dental, and vision; life insurance; critical illness insurance and accident insurance; disability benefits; retirement savings; paid time off (including vacation, holidays, and sick leave); and parental leave. Eligibility for benefits and specific offerings may vary based on position and employment status. To view more details of the benefits offered, visit Myrjbenefits.com.

At Raymond James our associates use five guiding behaviors (Develop, Collaborate, Decide, Deliver, Improve) to deliver on the firm's core values of client-first, integrity, independence and a conservative, long-term view.
We expect our associates at all levels to:
Grow professionally and inspire others to do the same
Work with and through others to achieve desired outcomes
Make prompt, pragmatic choices and act with the client in mind
Take ownership and hold themselves and others accountable for delivering results that matter
Contribute to the continuous evolution of the firm

At Raymond James - as part of our people-first culture, we honor, value, and respect the uniqueness, experiences, and backgrounds of all of our Associates. When associates bring their best authentic selves, our organization, clients, and communities thrive. The Company is an equal opportunity employer and makes all employment decisions on the basis of merit and business needs.