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Bank Computer Science Jobs in Texas (NOW HIRING)

TBK Bank, SSB

Director of Data Science

Dallas, TX · On-site

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

A Master's degree in Data Science, Statistics, Mathematics, Economics, Computer Science, or another relevant quantitative discipline is required. * 5-7 years of professional experience in data ...

Bank of America

Risk Process Analyst

Plano, TX · On-site

At Bank of America, we are guided by a common purpose to help make financial lives better through ... Finance, Economics, Mathematics, Computer Science, Statistics, Process and Mechanical Engineering ...

Bread Financial

Lead Data Scientist

Frisco, TX · On-site +1

$144K - $250K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Bachelor's Degree in Statistics, Mathematics, Engineering, Data Science, Computer Science, or ... Experience in bank card/credit card business, consulting, retail, marketing, loyalty, and/or ...

TBK Bank, SSB

Data Analyst

Dallas, TX

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

Join TBK Bank! At TBK Bank, a subsidiary of Triumph, we're a team of passionate, driven ... Bachelor's degree in Analytics, Business, Finance, Computer Science, or related field * 2-4 years ...

TBK Bank, SSB

Data Analyst

Dallas, TX · On-site

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

Join TBK Bank! At TBK Bank, a subsidiary of Triumph, we're a team of passionate, driven ... Bachelor's degree in Analytics, Business, Finance, Computer Science, or related field * 2-4 years ...

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Showing results 41-60

All JobsBank Computer Science JobsBank Computer Science Jobs in Texas

Bank Computer Science information

What is a bank computer scientist?

A Bank Computer Scientist is a technology professional who specializes in designing, developing, and maintaining computer systems and software used within the banking sector. Their responsibilities include ensuring the security of financial transactions, developing algorithms for fraud detection, and implementing reliable banking applications. They work closely with IT and security teams to keep banking systems running efficiently and securely. Their expertise helps banks adapt to new technologies and meet regulatory requirements.

How does a bank computer scientist typically collaborate with other departments in a banking environment?

In a banking environment, Computer Science professionals frequently work alongside teams from risk management, compliance, operations, and customer service to develop, test, and maintain secure and efficient banking systems. Collaboration often involves gathering requirements, troubleshooting issues, and integrating new technologies to support business goals. Effective communication and understanding of banking regulations are key, as projects may involve cross-functional meetings and ongoing coordination to ensure technological solutions align with industry standards and client needs.

What are the key skills and qualifications needed to thrive as a bank computer scientist, and why are they important?

To succeed as a Bank Computer Science professional, you need a solid background in computer science, programming languages (such as Java or Python), and knowledge of banking systems, often supported by a relevant degree. Familiarity with core banking software, cybersecurity practices, databases, and sometimes certifications like CISSP or CISM are typically required. Strong analytical thinking, attention to detail, and effective teamwork help address complex technical challenges and ensure secure, efficient operations. These skills are crucial for maintaining robust financial systems, safeguarding sensitive data, and supporting innovative banking solutions.

What is the difference between Bank Computer Science vs Bank IT Specialist?

AspectBank Computer ScienceBank IT Specialist
Required CredentialsBachelor's in Computer Science or related field, certifications like CompTIA, CiscoSimilar certifications, often with additional focus on network or security certifications
Work EnvironmentBank IT departments, software development teams, cybersecurity unitsBank branches, data centers, IT support teams within banks
Employer & Industry UsageFinancial institutions, banks, fintech companiesBanking institutions, financial service providers
Common Search & Comparison IntentUnderstanding roles in banking tech, career paths in bank ITJob responsibilities, certifications, and skills for bank IT roles

Bank Computer Science focuses on software development, system analysis, and cybersecurity within banks, often requiring programming skills and advanced technical knowledge. Bank IT Specialist typically handles hardware, network support, and troubleshooting in banking environments. Both roles share similar credentials and industry usage but differ in daily responsibilities and technical focus.

Can someone who studies computer science work in a bank?

Yes, a computer science graduate can work in a bank, often in roles such as software developer, cybersecurity analyst, or data analyst. Banks rely on computer science skills for developing financial software, managing data security, and maintaining banking systems, often requiring knowledge of programming languages, databases, and security protocols.

How is computer science used in banking?

Bank computer science professionals develop and maintain software systems that support banking operations, including transaction processing, fraud detection, and data security. They also work with databases, cybersecurity measures, and financial algorithms to ensure efficient and secure banking services.

What positions would you work in a bank with a computer science degree?

With a computer science degree, you can work in various bank roles such as software developer, systems analyst, cybersecurity specialist, data analyst, or IT support. These positions involve developing banking applications, managing security protocols, analyzing financial data, and maintaining IT infrastructure, often requiring knowledge of programming languages, databases, and security tools.

What are popular job titles related to Bank Computer Science jobs in Texas?

For Bank Computer Science jobs in Texas, the most frequently searched job titles are:

What job categories do people searching Bank Computer Science jobs in Texas look for?

The top searched job categories for Bank Computer Science jobs in Texas are:

What cities in Texas are hiring for Bank Computer Science jobs?

Cities in Texas with the most Bank Computer Science job openings:

Bank Computer Science jobs near you
Infographic showing various Bank Computer Science job openings in Texas as of August 2026, with employment types broken down into 1% As Needed, 85% Full Time, 11% Part Time, 2% Contract, and 1% Nights. Highlights an 76% Physical, 2% Hybrid, and 22% Remote job distribution.

Director of Data Science

TBK Bank, SSB

Dallas, TX • On-site

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 4 days ago

Job description

Join Triumph!
At Triumph, our vision is a world where freight transactions are accurate and seamless on the most modern and secure freight transaction network. That's why we're looking for passionate, innovative, solutions-oriented people to join our team. We thrive on providing exceptional customer service and we look for team members with an entrepreneurial spirit and a passion to build successful partnerships with our clients. Because at the end of the day our goal is to help our partners businesses run better.
Director of Data Science
Position Summary
We are seeking a Director of Data Science to design, build, and operationalize quantitative models that power both internal and customer-facing intelligence solutions. This role focuses on developing forecasting, optimization, and signal-based models that translate largescale transportation data into trusted insights for carriers, brokers, and shippers. In addition to hands-on technical leadership, this role may include managing data science talent and helping to scale the function over time as organizational needs evolve. The ideal candidate brings strong statistical rigor, experience working with real-world operational data, and a product-oriented mindset for deploying models that influence commercial and operational decisions across transportation networks.
Key Responsibilities
  • Develop and maintain forecasting and predictive models supporting transportation use cases such as pricing, demand forecasting, capacity trends, service performance, and network dynamics.
  • Build and scale the data science function, including hiring, onboarding, and managing direct reports as business needs evolve. Design and execute statistical modeling and experimentation, including hypothesis testing, A/B testing, and causal analysis to evaluate market and operational changes.
  • Build optimization and decision support models that inform routing, capacity allocation, pricing strategy, and operational trade-offs.
  • Lead signal development for transportation intelligence products, transforming raw transactional and network data into scalable, reliable indicators and indices.
  • Establish and lead model validation, performance monitoring, and governance frameworks to ensure stability, accuracy, and trustworthiness of production models.
  • Partner closely with product, analytics, and engineering teams to translate transportation domain needs into analytically sound, production ready models.
  • Document methodologies, assumptions, and limitations to support transparency, internal review, and customer facing confidence in intelligence outputs.
  • Continuously evaluate new data sources, modeling approaches, and techniques relevant to transportation, logistics, and network-based intelligence.

Required Qualifications
  • A Master's degree in Data Science, Statistics, Mathematics, Economics, Computer Science, or another relevant quantitative discipline is required.
  • 5-7 years of professional experience in data science, applied statistics, or quantitative analytics.
  • Strong experience with forecasting, predictive modeling, and statistical analysis in applied business contexts.
  • Demonstrated ability to build models that support decision making, optimization, or market intelligence.
  • Strong Python and SQL skills and experience working with large, complex datasets.
  • Experience validating models and monitoring performance in production environments. Direct experience with model governance frameworks.
  • Ability to clearly communicate quantitative insights to both technical and non-technical stakeholders.

Preferred Qualifications
  • Experience working with transportation, logistics, supply chain, or network-based data.
  • Strong expertise in
    • Regression & tree-based models (e.g., XGBoost, Random Forest)
    • Time series forecasting (e.g., SARIMAX, Prophet, TFT)
    • Statistical modeling of skewed distributions (e.g., log-normal, gamma)
  • 2 years in a leadership or people-management capacity
  • Deep understanding of freight market dynamics, including the interaction between spot and contract pricing, broker and carrier economics, and the impact of capacity cycles and seasonality on market behavior.
  • Familiarity with time-series modeling, signal processing, or index construction.
  • Experience supporting intelligence, analytics, or data products used by external customers.
  • Experience working with large-scale datasets in cloud environments and data pipelines (e.g., Snowflake, AWS, Sagemaker)

We offer Medical, Dental, Vision, Paid Time Off, 401k and much more.
Go on. Do it. Apply Today!

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