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Executive Data Science Jobs in Texas (NOW HIRING)

... to business and executive leadership, driving the development and deployment of intelligent ... Act as the technical lead for high-impact data science projects, from ideation through production ...

... to business and executive leadership, driving the development and deployment of intelligent ... Act as the technical lead for high-impact data science projects, from ideation through production ...

... to business and executive leadership, driving the development and deployment of intelligent ... Act as the technical lead for high-impact data science projects, from ideation through production ...

Data Scientist

Dallas, TX · On-site

$65 - $75/hr

Roles & Responsibilities 6+ years of experience in Machine Learning and Data Science. • Strong ... executive audiences. - Ability to adapt quickly to changing priorities and new technologies ...

Lead data science projects in close collaboration with IT, Data Engineering, Application ... executive leadership * Experience and proficiency with Python, deep learning frameworks (e.g ...

Lead data science projects in close collaboration with IT, Data Engineering, Application ... executive leadership * Experience and proficiency with Python, deep learning frameworks (e.g ...

Showing results 41-60

Executive Data Science information

See Texas salary details

$24.7K

$87.2K

$171.4K

How much do executive data science jobs pay per year?

As of Aug 21, 2026, the average yearly pay for executive data science in Texas is $87,158.00, according to ZipRecruiter salary data. Most workers in this role earn between $54,000.00 and $112,300.00 per year, depending on experience, location, and employer.

What is executive data science?

Executive Data Science refers to the leadership and management of data science initiatives within an organization. Professionals in this role are responsible for setting the strategic direction for data-driven projects, overseeing data teams, and ensuring that data science efforts align with business goals. They bridge the gap between technical teams and executives, translating analytical insights into actionable business strategies. Typically, Executive Data Scientists have a blend of technical expertise and strong business acumen, enabling them to make high-level decisions that impact the organization’s growth and innovation.

What skills and qualifications are needed to thrive as an executive data scientist?

To thrive as an Executive Data Scientist, you need deep expertise in statistics, machine learning, and data analysis, typically supported by an advanced degree in a quantitative field. Proficiency with data platforms (such as SQL, Hadoop, or Spark), programming languages (like Python or R), and familiarity with data visualization tools is essential, along with certifications like Certified Analytics Professional (CAP) being advantageous. Strategic vision, leadership, and the ability to communicate complex insights to non-technical stakeholders are vital soft skills. These competencies drive effective data-driven decision-making and ensure alignment between analytics initiatives and business objectives.

How does an executive data scientist typically collaborate with other departments to drive data-driven decision making?

Executive Data Scientists frequently work cross-functionally with departments such as marketing, product, finance, and operations to identify key business challenges and opportunities where data can provide strategic insights. They lead or advise interdisciplinary teams, translate complex analytics into actionable recommendations, and often present findings to senior leadership or stakeholders. Building strong relationships and understanding business objectives are crucial, as these collaborations enable the alignment of data science initiatives with organizational goals.

What is the difference between Executive Data Science vs Data Scientist?

AspectExecutive Data ScienceData Scientist
CredentialsAdvanced degrees (Master's/PhD), leadership experienceBachelor's or Master's in Data Science, Computer Science, or related fields
Work EnvironmentStrategic, leadership-focused, often in executive officesHands-on data analysis, modeling, coding in technical teams
Employer & Industry UsageSenior roles in tech, finance, consulting, and large organizationsTech companies, startups, research institutions, various industries

Executive Data Science roles focus on strategic decision-making, leadership, and overseeing data initiatives, while Data Scientists are primarily involved in technical data analysis and modeling. Both roles require strong analytical skills, but Executive Data Scientists combine technical expertise with leadership responsibilities.

What are the most commonly searched types of Data Science jobs in Texas?

The most popular types of Data Science jobs in Texas are:

What cities in Texas are hiring for Executive Data Science jobs?

Cities in Texas with the most Executive Data Science job openings:

Infographic showing various Executive Data Science job openings in Texas as of August 2026, with employment types broken down into 1% As Needed, 87% Full Time, 10% Part Time, and 2% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $87,158 per year, or $41.9 per hour.

Senior Data Scientist

SWBC

San Antonio, TX

Full-time

Medical, Retirement

Re-posted 24 days ago


SWBC rating

6.5

Company rating: 6.5 out of 10

Based on 17 frontline employees who took The Breakroom Quiz


Job description

SWBC is seeking a talented individual who will lead the development of our most critical and complex machine learning and AI initiatives. This role is a technical leadership position responsible for setting the strategic direction for data science projects, mentoring the Data Science team, and ensuring our models are scalable, reliable, and directly tied to business outcomes. The Senior Data Scientist will serve as a subject matter expert and strategic partner to business and executive leadership, driving the development and deployment of intelligent solutions across SWBC's enterprise AI/ML platform.

Why you'll love this role:

In this role, you will lead the design and delivery of intelligent solutions that power Clara, SWBC's AI decision assistant, and drive enterprise-wide analytics through forecasting models, segmentation analysis, and context engineering for AI self-service. Your daily work will center on developing and deploying within SWBC Intelligence, our multi-model AI orchestration platform spanning AWS Bedrock, AWS Sagemaker, alongside Hex for experimentation and Omni for AI context development powering Clara and SWBC Insights.

Essential duties include the following:

  • Act as the technical lead for high-impact data science projects, from ideation through production deployment, ensuring alignment with business objectives and compliance standards.
  • Design and implement machine learning and AI solutions, including predictive models, forecasting frameworks, segmentation analysis, and natural language processing capabilities.
  • Lead the development and enhancement of Clara, SWBC's AI decision assistant, including context engineering within Omni, model evaluation, and continuous intelligence improvement.
  • Develop and deploy AI/ML solutions within SWBC Intelligence, the enterprise multi-model AI orchestration platform, leveraging AWS Bedrock and AWS Sagemaker for internal and client-facing use cases.
  • Build and maintain AI/ML experiment workflows using Hex for prototyping and exploration, and AWS SageMaker and MLflow for experiment tracking, model versioning, and lifecycle management within the platform.
  • Contribute to the platform's Evaluation Harness process, including golden dataset curation, rubric-based scoring, adversarial testing, and model performance benchmarking to ensure solution quality before production deployment.
  • Conduct AI experimentation and prototyping within governed sandbox environments, including Snowflake Sandbox and Hex, while adhering to data privacy, masking, and compliance requirements.
  • Collaborate with Analytics Engineers and Data Management teams to source model training data from governed medallion layers (Bronze Silver Gold), ensuring data quality and lineage traceability.
  • Champion Responsible AI practices, including explainability, bias monitoring, fairness metrics, and model auditability in alignment with SWBC's governance framework.
  • Lead model validation, A/B testing, and performance monitoring to ensure models meet business requirements and maintain production-grade reliability.
  • Partner with IT platform engineering teams to provide feedback on platform capabilities, identify gaps, and advocate for enhancements that improve the Data Science team's development and deployment experience.
  • Mentor, coach, and provide technical guidance to the Data Science team, fostering a culture of continuous learning, empirical rigor, and innovation.
  • Publish technical documentation and best practices to advance the team's capabilities and contribute to the organization's knowledge base.


Serious candidates will possess the minimum qualifications:

  • Master's or Ph.D. in a quantitative field such as Computer Science, Data Science, Statistics, Mathematics, or a related discipline. Equivalent professional experience (8+ years) may be considered in lieu of an advanced degree.
  • Minimum five (5) years of progressive experience in data science, with a portfolio of deployed models that have driven significant business value.
  • Extensive experience with advanced machine learning techniques, including deep learning, natural language processing (NLP), time series forecasting, or computer vision.
  • Proficiency in Python and strong understanding of ML frameworks such as TensorFlow, PyTorch, scikit-learn, or equivalent.
  • Hands-on experience developing and deploying models within cloud-based AI/ML platforms, including AWS SageMaker, Bedrock, and S3.
  • Experience with MLOps tools and practices, including MLflow, model registries, CI/CD for ML pipelines, and automated evaluation frameworks.
  • Proficiency in Hex for data science experimentation and prototyping, and familiarity with Omni for analytics and AI context development.
  • Familiarity with Snowflake for data sourcing and analytics within a governed medallion architecture.
  • Strong understanding of data governance, compliance, and responsible AI principles within regulated industries. Financial services or insurance experience preferred.
  • Exceptional communication and leadership skills, with a track record of influencing strategic decisions and presenting complex findings to non-technical stakeholders.
  • Demonstrated ability to work autonomously, manage projects, and make key decisions with minimal guidance.
  • Ability to lift 20 lbs. of files, supplies, documents, or other related items.

SWBC offers*:

  • Competitive overall compensation package
  • Work/Life balance
  • Employee engagement activities and recognition awards
  • Years of Service awards
  • Career enhancement and growth opportunities
  • Leadership Academy and Mentor Program
  • Continuing education and career certifications
  • Variety of healthcare coverage options
  • Traditional and Roth 401(k) retirement plans
  • Lucrative Wellness Program

*Based upon employee eligibility

Additional Information:

SWBC is a Substance-Free Workplace and requires pre-employment drug testing.

Please note, SWBC does not hire tobacco users as allowed by law.

To learn more about SWBC, visit our website at www.SWBC.com. If interested, please click the appropriate apply button.


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