1

Executive Data Science Jobs in Texas (NOW HIRING)

Architect, Data Science

Arlington, TX · On-site

$155 - $190/hr

As part of our growing Data Science practice, this role offers an exciting opportunity to lead ... executives. Note: This position is not eligible for work sponsorship at this time. Primary ...

Data Science Analyst II

San Antonio, TX · On-site

$80 - $120/hr

Data Science Analyst II Hiring Department: Dell Medical School Position Open To: All Applicants ... Ability to communicate technical concepts to clinical, operational, and executive audiences. Strong ...

New

Create executive-ready narratives, visualizations, and recommendations that connect technical ... You make data science more accessible to the business through better tools, communication, and ...

Interpret simulation results and large datasets, delivering actionable insights to executive and ... Master-level data science industry knowledge and knowledge of the insurance marketplace. What would ...

AI Engineer, Data Science

Austin, TX · On-site

$113K - $136K/yr

Collaborate closely with engineering, product, and executive stakeholders to deliver innovative, production-ready solutions * Mentor and uplift junior data scientists, setting standards for ...

next page

Showing results 1-20

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.

Architect, Data Science

Socket.dev

Arlington, TX • On-site

$155 - $190/hr

Other

Posted 14 days ago


Job description

Founded in 2017, Lovelytics has helped some of the most complex enterprises across industries such as Energy & Utilities, Media & Entertainment, Manufacturing and Retail & CPG, modernize their data and put AI to work, not in a deck, but in production. We move fast, stay close to the cutting edge, and care more about outcomes than optics.

Our work spans the full data and AI lifecycle: Data Strategy & Advisory, Data Engineering, Analytics & Visualization, Generative AI & ML, and Cloud Migration & Modernization — all delivered on Databricks, with deep partnerships across AWS, Azure, and GCP. To date, we've delivered over $2B in business value for Fortune 500 clients.

In the last year, Lovelytics as grown from 85 to 500+ people across the Americas, all while keeping the technically excellent, low-ego culture that makes the work worth doing, earning us a Best Places to Work recognition and a spot among Databricks' top partners.

Lovelytics is seeking a Solutions Architect – Data Science with hands‑on experience delivering client‑facing, enterprise‑grade machine learning and advanced analytics solutions, particularly on the Databricks platform. As part of our growing Data Science practice, this role offers an exciting opportunity to lead technical strategy, design end‑to‑end ML pipelines, and drive pre‑sales engagements from initial scoping to final delivery.

The Solutions Architect will play a role in defining business‑value metrics, shaping client proposals, and directing cross‑functional delivery teams to build scalable, high‑impact AI/ML applications. Our ideal candidate blends deep technical expertise across predictive modeling and modern LLM frameworks with seasoned consulting acumen to influence both technical execution teams and C‑suite executives.

Note: This position is not eligible for work sponsorship at this time.

Primary Responsibilities:
  • Define clear business‑value metrics (e.g., ROI, revenue impact, cost reduction) alongside technical performance targets for every engagement.
  • Lead technical scoping, feasibility assessments, and solution design for proposals, Statements of Work, and client pitches.
  • Design scalable, secure, and maintainable end‑to‑end ML pipelines, spanning data analysis, feature engineering, model training, deployment, and MLOps.
  • Direct cross‑functional delivery teams of Data Scientists, Data Engineers, and ML Engineers to execute solutions aligned with architectural standards.
  • Establish code quality standards, model validation protocols, and technical best practices to prevent technical debt and ensure system reliability.
  • Articulate technical concepts, model trade‑offs, and operational risks clearly to both technical teams and non‑technical C‑suite stakeholders.
  • Design operational workflows and user integration strategies to drive high adoption of AI/ML tools among end‑users.
  • Conduct client enablement workshops and knowledge transfer sessions to build internal capability and ensure long‑term solution sustainability.
  • Build rapid prototypes, technical pre‑sales presentations, and proof of concepts for prospective client engagements.
Our Ideal Candidate's Skills and Experiences:
  • B.S. or M.S. in Computer Science, Engineering, Economics, or a related quantitative field.
  • 7+ years of experience in Data Science & AI/ML, including large‑scale solution deployments.
  • 4+ years in a client‑facing role, preferably in a professional services firm.
  • Proven track record designing and implementing modern data science solutions in at least two of the following areas: forecasting, anomaly detection, recommendation systems, computer vision, propensity modeling, and mathematical optimization.
  • Expert knowledge of Python and SQL and strong hands‑on experience with Databricks (Unity Catalog, MLFlow, Delta Tables, etc.).
  • Proficiency with commercial and open‑source LLM APIs and tooling like Hugging Face Transformers, LangChain, etc.
  • Experience with rapid prototyping and creating proofs of concept, technical pre‑sales presentations, and pricing for engagements.
  • Strong client‑facing communication skills with the ability to influence technical and executive stakeholders.
  • Prior experience with fraud detection, risk modeling, or anomaly prevention systems.
What We Promise You:
  • Meaningful, cutting‑edge projects in Generative AI with clients across industries—from Fortune 100 firms to disruptive startups.
  • Rapid learning and mentorship opportunities with AI/GenAI thought leaders and practitioners.
  • A culture of experimentation, innovation, and continuous improvement.
  • Opportunity to be a conference speaker, blogger, writer.
  • A diverse, inclusive team and one of the best GenAI teams, where your voice, ideas, and

The base salary range for this position for candidates based in the US is $155,000-190,000 per year. Compensation is determined based on a variety of factors including, but not limited to, relevant experience, skills, qualifications, scope of role and budget. Candidates are not guaranteed to be placed at any particular point within the range, and most offers will fall within the middle of the range or below. Lovelytics is committed to pay equity and transparency in compensation practices.

Remote Roles $155,000 — $190,000 USD

Lovelytics is an Equal Opportunity Employer. This means you don’t have to worry about whether your application process will be fair. We consider all applicants without regard to race, color, religion, age, ancestry, ethnicity, gender, gender identity, gender expression, sexual orientation, veteran status, or disability.

#J-18808-Ljbffr