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Banking Domain Testing Jobs in Texas (NOW HIRING)

iShare Inc

SENIOR MODELING LEAD

Houston, TX · On-site

Relevant Team Lead experience (at least 3 years)in Banking domain * Hands on experience in Model ... and bias testing protocols across team. * Act as a primary escalation point for model risk ...

Frost Bank

Software Engineer III - Open Banking

Austin, TX

$57 - $76.50/hr

In this role, you will be responsible for designing, writing, testing, implementing, supporting ... Strong knowledge of Domain-Driven Design (DDD) and distributed systems. * Hands-on experience with ...

Frost Bank

Software Engineer III - Open Banking

Dallas, TX

$57 - $76.50/hr

In this role, you will be responsible for designing, writing, testing, implementing, supporting ... Strong knowledge of Domain-Driven Design (DDD) and distributed systems. * Hands-on experience with ...

Cognizant

Generative AI Lead Engineer

Dallas, TX · On-site

$120 - $140/hr

... testing, deployment, and code reviews) * Develop scalable architectures leveraging Retrieval ... Banking domain experience Compensation The annual salary for this position ranges from $120,000 to ...

iShare, Inc.

SENIOR MODELING LEAD

Houston, TX · On-site

$145K - $165K/yr

Relevant Team Lead experience (at least 3 years)in Banking domain * Hands on experience in Model ... and bias testing protocols across team. * Act as a primary escalation point for model risk ...

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Banking Domain Testing information

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How much do banking domain testing jobs pay per hour?

As of Aug 15, 2026, the average hourly pay for banking domain testing in Texas is $41.39, according to ZipRecruiter salary data. Most workers in this role earn between $36.97 and $46.83 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in banking domain testing, and why are they important?

To thrive in Banking Domain Testing, you need a strong understanding of banking processes, regulatory requirements, and software testing methodologies, usually supported by a degree in computer science or finance. Experience with test management tools (like HP ALM or JIRA), automation frameworks, and domain-specific certifications such as ISTQB or CBAP are highly valued. Analytical thinking, attention to detail, and effective communication are essential soft skills for success in this field. These competencies ensure accurate risk identification, regulatory compliance, and seamless collaboration across technology and banking teams.

What are some common challenges faced in banking domain testing, and how can they be addressed?

One of the most common challenges in Banking Domain Testing is keeping up with rapidly changing regulatory requirements and complex banking workflows. Testers often need to thoroughly validate multiple integrations between core banking systems, payment gateways, and external regulatory agencies, which can be both technically and procedurally demanding. Clear documentation, proactive communication with business analysts, and continuous learning are vital for overcoming these obstacles. Additionally, collaborating closely with development and product teams helps ensure any issues are detected and resolved early, resulting in higher software quality and compliance.

What is banking domain testing?

A Banking Domain Testing job involves verifying the functionality, security, and performance of banking applications to ensure they meet industry standards and compliance requirements. Testers work on various banking modules such as payments, loans, credit cards, and internet banking, identifying defects and ensuring seamless transactions. They use manual and automated testing techniques to validate core banking processes, regulatory compliance, and data integrity. This role requires knowledge of banking operations, financial regulations, and testing tools to ensure high-quality software deployment in the financial sector.

What are the most commonly searched types of Banking Domain Testing jobs in Texas?

The most popular types of Banking Domain Testing jobs in Texas are:

What are popular job titles related to Banking Domain Testing jobs in Texas?

For Banking Domain Testing jobs in Texas, the most frequently searched job titles are:

What job categories do people searching Banking Domain Testing jobs in Texas look for?

The top searched job categories for Banking Domain Testing jobs in Texas are:

What cities in Texas are hiring for Banking Domain Testing jobs?

Cities in Texas with the most Banking Domain Testing job openings:

Banking Domain Testing jobs near you
Infographic showing various Banking Domain Testing job openings in Texas as of August 2026, with employment types broken down into 61% Full Time, and 39% Contract. Highlights an 89% In-person, and 11% Remote job distribution, with an average salary of $86,101 per year, or $41.4 per hour.

SENIOR MODELING LEAD

iShare Inc

Houston, TX • On-site

Full-time

Re-posted 23 days ago

Job description

 
Position: SENIOR MODELING LEAD
YEARS OF EXPERIENCE: 9-10+ YEARS
Location: Plano, TX & San Antonio, TX
Salary range: $145k-$165K+12% Incentive & Benefits.
 
Position Overview
We are seeking a Senior Modeling Lead to provide strategic and technical oversight across multiple AI/ML workstreams. In this role, you will direct a team of data scientists / modelers through full model development lifecycle, ensure consistency in modeling standards and governance practices, and serve as primary liaison between technical teams and senior stakeholders. Ideal candidate brings 9-10+ years of modeling experience and a proven ability to operate effectively at both strategic and technical levels.
 
  1. Relevant Team Lead experience (at least 3 years)in Banking domain
  2. Hands on experience in Model Development, Model Monitoring of advanced ML/quantitative/finance models
  3. Strong proficiency in Python; familiarity with modern AI/ML frameworks, ML-Ops, and large-scale data platforms.
 
Key Responsibilities
  • Provide strategic and technical leadership across multiple AI/ML modeling workstreams, ensuring alignment with business
  • Oversee full model lifecycle across all workstreams — including development, validation, independent assessment, performance optimization, monitoring, documentation, and governance.
  • Establish and enforce consistent modeling standards, methodology frameworks, explainability practices, and bias testing protocols across team.
  • Act as a primary escalation point for model risk, governance issues, technical challenges, partnering with risk, compliance as needed.
  • Lead model review and approval processes, ensuring all models meet internal governance requirements and applicable regulatory standards.
  • Translate complex modeling outcomes and technical findings into clear, actionable insights for executive and non-technical stakeholders.
  • Drive evaluation and adoption of emerging AI/ML tools, platforms, and methodologies, providing evidence-based recommendations to leadership.
  • Recruit, mentor, and develop a high-performing team of senior and mid-level modelers, fostering a culture of technical rigor and continuous improvement.
  • Define team's long-term analytical roadmap, balancing innovation with BAU delivery.
  • Collaborate cross-functionally with data engineering, technology, operations, and business teams to align modeling solutions with broader organizational objectives.
Qualifications & Experience
  • 10+ years of progressive experience in quantitative modeling, data science, or applied AI/ML, with at least 3 years in a team leadership or senior technical lead capacity.
  • Broad expertise across multiple modeling domains, such as predictive analytics, NLP, optimization, or AI platform evaluation.
  • Strong proficiency in Python; familiarity with modern AI/ML frameworks, MLOps tooling, and large-scale data platforms.
  • Deep understanding of end-to-end model lifecycle, including model risk management, validation frameworks, and regulatory expectations.
  • Proven ability to lead and develop cross-functional modeling teams in a fast-paced, delivery-oriented environment.
  • Experience engaging with model risk, audit, compliance, or regulatory stakeholders, and navigating governance and approval processes.
  • Exceptional communication skills & ability to present complex technical concepts clearly to stakeholders.
  • Track record of driving adoption of emerging AI/ML technologies in a structured manner.
  • Advanced degree (Master’s or PhD) in Statistics, Computer Science, Mathematics, Data Science, or a related quantitative discipline preferred.