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Computer Science Banking Jobs (NOW HIRING)

... Bank (RCSB PDB, RCSB.org) and the opportunity to be part of a leadership team building a new ... computer science, statistics, or related field; made outstanding contributions in basic/applied ...

As a Data Scientist within PNC's Corporate and Institutional Banking (C&IB) organization, you will ... Master's degree in quantitative fields (Computer Science, Data Science, Machine Learning ...

TBK Bank, SSB is seeking a Director of Data Science to design, build, and operationalize ... Required : • A Master's degree in Data Science, Statistics, Mathematics, Economics, Computer ...

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Computer Science Banking information

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$20.5K

$67.9K

$141.5K

How much do computer science banking jobs pay per year?

As of Jul 14, 2026, the average yearly pay for computer science banking in the United States is $67,884.00, according to ZipRecruiter salary data. Most workers in this role earn between $40,500.00 and $94,000.00 per year, depending on experience, location, and employer.

Which CS field has the highest salary?

In computer science, fields such as artificial intelligence, machine learning, and data science tend to have the highest salaries due to high demand and specialized skills. Roles involving cybersecurity and software engineering also offer high compensation, especially with advanced certifications and experience.

What types of projects do professionals in Computer Science Banking typically work on?

Professionals in Computer Science Banking often work on projects such as developing secure online banking platforms, implementing fraud detection systems, optimizing transaction processes, and managing large financial data sets. They may also support regulatory compliance projects and enhance cybersecurity measures to protect sensitive customer information. Collaboration with financial analysts, management, and IT teams is common, as is involvement in implementing emerging technologies like artificial intelligence or blockchain. This dynamic environment provides valuable experience across technical and financial domains and supports career advancement into senior technical or leadership roles.

Is computer science good for banking?

Computer science is highly relevant for banking roles, especially in areas like financial technology, data analysis, cybersecurity, and software development. Professionals with programming skills, knowledge of databases, and understanding of financial systems are in demand to improve efficiency, security, and innovation within banks.

What is the use of computer science in banking?

Computer science in banking involves developing and maintaining software systems for transactions, data management, and security. It enables automation, fraud detection, risk analysis, and customer service through technologies like databases, cybersecurity, and programming languages.

What is a Computer Science Banking job?

A Computer Science Banking job involves applying computer science principles to develop, maintain, and secure banking systems. Professionals in this field work on digital banking platforms, cybersecurity, data analytics, and financial software development. They help banks enhance customer experience, prevent fraud, and optimize operations through technology. Roles may include software developers, cybersecurity analysts, data scientists, and IT specialists in financial institutions. These jobs require expertise in programming, databases, encryption, and financial technologies.

What are the key skills and qualifications needed to thrive in the Computer Science Banking position, and why are they important?

To excel in a Computer Science Banking role, you need a strong background in computer science principles, programming, and data analysis, ideally supported by a relevant degree or certifications. Familiarity with banking software platforms, cybersecurity protocols, databases, and tools like Python, SQL, or Java are often required. Strong problem-solving skills, attention to detail, and clear communication help you work effectively with both technical teams and finance professionals. These competencies ensure secure, efficient, and innovative technology solutions within the fast-paced and highly regulated banking sector.

Is computer science dead due to AI?

Computer science jobs, including roles in banking technology, continue to be in demand as AI advances, requiring skills in programming, data analysis, and system design. AI tools often complement rather than replace core computer science functions, emphasizing the importance of ongoing learning and adaptability for professionals in the field.
More about Computer Science Banking jobs
What cities are hiring for Computer Science Banking jobs? Cities with the most Computer Science Banking job openings:
What are the most commonly searched types of Computer Science Banking jobs? The most popular types of Computer Science Banking jobs are:
What states have the most Computer Science Banking jobs? States with the most job openings for Computer Science Banking jobs include:
What job categories do people searching Computer Science Banking jobs look for? The top searched job categories for Computer Science Banking jobs are:
Infographic showing various Computer Science Banking job openings in the United States as of July 2026, with employment types broken down into 1% As Needed, 87% Full Time, 9% Part Time, and 3% Contract. Highlights an 89% Physical, 4% Hybrid, and 7% Remote job distribution, with an average salary of $67,884 per year, or $32.6 per hour.
M&A Quant Advisory - Vice President - Investment Banking - New York

M&A Quant Advisory - Vice President - Investment Banking - New York

Goldman Sachs

New York, NY • On-site

Other

Re-posted 28 days ago


Goldman Sachs rating

8.2

Company rating: 8.2 out of 10

Based on 26 frontline employees who took The Breakroom Quiz

44th of 149 rated banks


Job description

M&A Quant Advisory - Vice President - Investment Banking 

The M&A Quant Advisory team is an integral part of the Goldman Sachs Mergers & Acquisitions ("M&A") advisory business, responsible for developing quantitative models and technologies to solve complex business problems. As a key pillar of the firm's M&A business, members of M&A Quant Advisory team use their mathematical and scientific training to advise clients on transactions, identify market opportunities, and help answer complex and data-driven questions. The team has a broad mandate, working closely with our banking teams to pitch and execute mergers and separations across sectors, market caps, and geographies.
Investment Banking Strats are both investment bankers and innovators who create analytics and scalable technology platforms that will shape the future of investment banking and how we connect with clients. Direct participation in client interactions, deal executions, and other core commercial activities allows us to be in the optimal position to develop technical innovations that create economic leverage and differentiate the firm. We ensure maximum technical efficacy by encouraging fluency in the latest quantitative models, data science, data engineering, and software platforms through peer learning, MOOC-like curated learning, and online training resources. 

Our team members are quantitative engineers, financial engineers, and data scientists who share a passion for investment banking and the financial markets.

Job Summary & Responsibilities

We are looking for an Vice President to join the Investment Banking M&A Quant Advisory team in New York. This is a banking role which predominantly covers the M&A and industry coverage groups within Investment Banking.

The position involves solving business, data, and technology-related problems across the business, using large and complex financial datasets, and working in tandem with Investment Bankers across different industry and product groups. The role requires a combination of the following competencies: an understanding of the financial markets, M&A, equity and debt products, strong quantitative modelling skills, strong communication skills with non-technical clients and bankers, data and statistical analysis including machine learning, and software engineering.

A successful candidate must act as a local liaison with our global team, and interact with the Classic Banking, Capital Solutions Group, and Global Markets teams. We expect them to be self-led, entrepreneurial, and capable of managing the delivery and adoption of key products. 

Responsibilities

  • Develop and deliver actionable insights and solutions for internal and external clients, including deal performance evaluation, competitive landscape analysis, and execution strategy.
  • Communicate the team's analyses and recommendations clearly to Investment Banking clients, tailoring content for non-technical audiences.
  • Design and implement advanced quantitative and analytical methodologies to identify and prioritize new transaction opportunities.
  • Build and maintain analytical codebases in Python (and other relevant languages), leveraging machine learning and statistical techniques.
  • Source, build, and maintain high-quality datasets from multiple vendors by partnering with data providers and designing robust data pipelines, database schemas, and storage/integration solutions; deliver curated datasets aligned to distinct business use cases.

Basic Qualifications

  • Bachelor's or advanced degree in a quantitative/ STEM discipline (e.g., Mathematics, Computer Science, Engineering, Statistics etc.)
  • Strong quantitative / analytic reasoning and problem-solving abilities 
  • Strong technical and computer programming skills in an Object-oriented programming language such as Python or Java
  • Strong data management skills in data querying languages including SQL, MongoDB, and NoSQL, and extracting large quantities of data from different data sources
  • Strong oral and written communication skills 
  • Strong interpersonal skills; desire and ability to play on a team 
  • Strong interest in finance, investment banking, and the capital markets 
  • Results-oriented work ethic based upon responsibility, enthusiasm, and pride in work 

Preferred Qualifications

  • 5+ years of quantitative modeling and development experience
  • 5+ years of working experience in finance, investment banking and / or capital markets

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About Goldman Sachs

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At Goldman Sachs, we commit our people, capital and ideas to help our clients, shareholders and the communities we serve to grow. Founded in 1869, we are a leading global investment banking, securities and investment management firm. Headquartered in New York, we maintain offices around the world. We believe who you are makes you better at what you do. We're committed to fostering and advancing diversity and inclusion in our own workplace and beyond by ensuring every individual within our firm has a number of opportunities to grow professionally and personally, from our training and development opportunities and firmwide networks to benefits, wellness and personal finance offerings and mindfulness programs.

Industry

Finance and insurance

Company size

10,000+ Employees

Headquarters location

New York, NY, US

Year founded

1869