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Data Scientist Machine Learning Jobs in Texas (NOW HIRING)

Senior Data Scientist

Austin, TX · On-site

$180 - $240/hr

Schwab's AI & Data Science organization helps shape the future of client and employee experiences through advanced analytics, machine learning, and generative AI. As a Senior AI & Data Scientist, you ...

Senior Data Scientist

Austin, TX · On-site

$155K - $200K/yr

Schwab's AI & Data Science organization helps shape the future of client and employee experiences through advanced analytics, machine learning, and generative AI. As a Senior AI & Data Scientist, you ...

Data Scientist II

Shavano Park, TX · On-site

$80 - $100/hr

The Data Scientist II is expected to independently lead analyses and model development projects ... Design, develop, and deploy machine learning models and analytical solutions to address business ...

New

Develop and implement machine learning algorithms to solve complex business problems. * Analyze ... Data Science Statistical Modeling * GenAI / Generative AI * LLMs * RAG * Agentic AI / AI Agents

As a Data Scientist, you will apply strong expertise through the use of machine learning, data mining, and information retrieval to design, prototype, and build next generation advanced analytics ...

Data Scientist

Dallas, TX · On-site

$65 - $75/hr

Roles & Responsibilities 6+ years of experience in Machine Learning and Data Science. • Strong understanding of Generative AI, Retrieval Augmented Generation, Agentic Workflow, Statistical methods ...

SWBC is seeking a talented individual who will contribute to the development of machine learning ... The Data Scientist II is expected to independently lead analyses and model development projects ...

SWBC is seeking a talented individual who will contribute to the development of machine learning ... The Data Scientist II is expected to independently lead analyses and model development projects ...

SWBC is seeking a talented individual who will contribute to the development of machine learning ... The Data Scientist II is expected to independently lead analyses and model development projects ...

Schwab's AI & Data Science organization helps shape the future of client and employee experiences through advanced analytics, machine learning, and generative AI. As a Senior AI & Data Scientist, you ...

Lead Data Scientist Location: Houston, TX 77002 Job Type: Full-Time Category: Non-Clinical ... Apply machine learning and statistical models to key business metrics and operational challenges.

New

Data Scientist Location : Austin, TX (Day One Onsite to Client Location) H-1B transfers are ... Experience with machine learning and LLMs is a strong plus. Key Responsibilities • Clean ...

New

Translate business problems into well-defined machine learning and predictive modeling objectives. * Collect, clean, transform, and analyze structured and unstructured data from multiple sources.

Showing results 21-40

Data Scientist Machine Learning information

See Texas salary details

$34.9K

$114.3K

$183.1K

How much do data scientist machine learning jobs pay per year?

As of Sep 2, 2026, the average yearly pay for data scientist machine learning in Texas is $114,350.00, according to ZipRecruiter salary data. Most workers in this role earn between $91,800.00 and $126,700.00 per year, depending on experience, location, and employer.

What is a data scientist machine learning?

A Data Scientist specializing in Machine Learning (ML) uses statistical methods, algorithms, and computational power to analyze data and create predictive models. They work with large datasets to identify patterns, train machine learning models, and improve decision-making processes. Responsibilities often include data cleaning, feature engineering, model selection, and performance evaluation. They may collaborate with engineers and business teams to deploy models in real-world applications. Strong skills in programming (Python, R), ML frameworks (TensorFlow, Scikit-learn), and data visualization are essential.

What are the typical day-to-day responsibilities of a data scientist machine learning?

On a typical day, a Data Scientist specializing in Machine Learning might gather and preprocess data, design and implement machine learning models, and evaluate their performance to solve real-world problems. They often collaborate with data engineers, software developers, and business stakeholders to translate business objectives into technical solutions and integrate models into existing systems. Other responsibilities can include visualizing data insights, conducting experiments to tune algorithms, and staying current with new developments in the field. The work is highly collaborative and iterative, requiring clear communication with various teams to ensure project goals are met efficiently.

What are the key skills and qualifications needed to thrive in the data scientist machine learning position, and why are they important?

To excel as a Data Scientist Machine Learning, you need a strong proficiency in statistics, programming (typically Python or R), and a solid understanding of machine learning algorithms, usually backed by a degree in computer science, mathematics, or a related field. Familiarity with tools such as TensorFlow, scikit-learn, SQL databases, and cloud platforms, as well as certifications in data science or machine learning, is commonly expected. Analytical thinking, problem-solving skills, and effective communication are vital soft skills in this profession. These qualifications combine to drive impactful insights and enable the successful development and deployment of machine learning models in business environments.

What is the salary of data scientist in machine learning?

The salary of a data scientist specializing in machine learning typically ranges from $90,000 to $150,000 annually, depending on experience, location, and industry. Senior roles or those with advanced skills in programming, statistical analysis, and tools like Python or TensorFlow may earn higher compensation.

What are the most commonly searched types of Data Scientist Machine Learning jobs in Texas?

The most popular types of Data Scientist Machine Learning jobs in Texas are:

What job categories do people searching Data Scientist Machine Learning jobs in Texas look for?

The top searched job categories for Data Scientist Machine Learning jobs in Texas are:

What cities in Texas are hiring for Data Scientist Machine Learning jobs?

Cities in Texas with the most Data Scientist Machine Learning job openings:

Infographic showing various Data Scientist Machine Learning job openings in Texas as of August 2026, with employment types broken down into 1% As Needed, 83% Full Time, 11% Part Time, 4% Contract, and 1% Nights. Highlights an 84% Physical, 4% Hybrid, and 12% Remote job distribution, with an average salary of $114,350 per year, or $55 per hour.

General Manager, Data Science & Machine Learning

Toyota

Plano, TX • On-site

Full-time

Medical, Retirement, PTO

Posted 22 days ago


Toyota rating

7.2

Company rating: 7.2 out of 10

Based on 876 frontline employees who took The Breakroom Quiz

23rd of 45 rated automakers


Job description

Overview

Who we are

Collaborative. Respectful. A place to dream and do. These are just a few words that describe what life is like at Toyota. As one of the world's most admired brands, Toyota is growing and leading the future of mobility through innovative, high-quality solutions designed to enhance lives and delight those we serve. We're looking for talented team members who want to Dream. Do. Grow. with us.

An important part of the Toyota family is Toyota Financial Services (TFS), the finance and insurance brand for Toyota and Lexus in North America. While TFS is a separate business entity, it is an essential part of this world-changing company- delivering on Toyota's vision to move people beyond what's possible. At TFS, you will help create best-in-class customer experience in an innovative, collaborative environment.

Toyota does not offer support or sponsorship of job applicants for employment-based visas or any other work authorization for this role now or in the future. You must have the right to work in the United States and not require Toyota support or sponsorship for immigration-related employment (e.g., H-1B, O-1, E-3, H-1B1, TN, F-1 OPT, F-1 STEM OPT, F-1 CPT, 'job flexibility benefits' [also known as I-140 or Adjustment of Status portability], etc.) now or in the future. You should not apply for this role if you will require Toyota to assist with immigration support or sponsorship now or in the future.

Who we're looking for

Toyota Financial Services is looking for a passionate and highly motivated General Manager, Data Science & Machine Learning. Reporting to the Vice President of Risk, this role will define, develop, deploy, and scale analytical, data science, machine learning, and application capabilities across TFS.

The General Manager leads a large enterprise data science and machine learning organization by setting technical direction, establishing standards for model development and deployment, and ensuring strong governance, compliance, and operational rigor. The position is responsible for delivering reliable, scalable analytical solutions that drive business value, partnering with business leaders to define decision-support capabilities, and building a strong talent pipeline to advance the organization's technical and leadership capabilities. In addition, this role works closely with business and technology executives to identify, prioritize, and deliver analytics and machine learning initiatives that create meaningful enterprise value. It translates complex business challenges into strategic roadmaps, investment priorities, and measurable delivery plans, while influencing decisions that shape how the enterprise allocates resources, manages risk, and pursues growth opportunities. The role also defines the long-term strategy for data science and machine learning engineering capabilities, including talent, platforms, governance, and business engagement, and represents the organization in executive planning, budgeting, and governance discussions. The position collaborates across risk, audit, compliance, finance, and technology to manage model risk, operational risk, and regulatory exposure.

The person in this role also serves as a subject matter expert on technical requirements and data team needs and is accountable for key decisions across the organization. This includes determining which initiatives to advance based on customer input and partnership, making pricing and strategic decisions as a member of the VPP Working Group, deciding on model implementation as a member of ASOP, and helping establish governance standards for model development as a member of the Model Governance Council. The General Manager is also responsible for decisions related to the promotion of data scientists.

This position is based at our North American headquarters in Plano, Texas. The selected candidate will be expected to reside within commutable distance of this location.

What you'll be doing

Leadership & Team Management

  • Lead a unified, 60-person, multi-level enterprise organization spanning data science and machine learning engineering, including senior leaders, managers, senior individual contributors, and technical teams.

  • Define and lead a talent strategy for attracting, assessing, hiring, and retaining exceptional technical and leadership talent within the constraints of the enterprise.

  • Develop learning programs for Data Science.

Enterprise Strategy & Technical Direction

  • Set enterprise standards and technical direction across modeling, experimentation, deployment, monitoring, and governance.

  • Ensure analytical and machine learning systems are designed as reliable, auditable, end-to-end decision systems.

  • Establish high standards for reproducibility, data quality, code quality, validation, release readiness, and production support.

  • Oversee the full progression of work from problem framing and prototype development through production deployment, adoption, and continuous improvement.

Product, Platform & Solution Delivery

  • Guide the development of production-grade solutions on modern cloud-based platforms such as AWS and Snowflake.

  • Lead delivery of a broad portfolio of analytical assets and applications, ranging from best-in-class predictive decisioning models to end-to-end business solutions with intuitive interfaces, configurable workflows, embedded analytics, reporting, and enterprise system integration.

  • Product ownership responsibilities for Pricing.

Business Partnership & Value Creation

  • Partner with executives and business leaders to define decision-support capabilities that improve business outcomes, customer experience, and operational effectiveness. These stakeholders can include risk, audit, compliance, finance, and technology to manage model risk, operational risk, and regulatory exposure.

Risk, Compliance & Governance

  • Ensure regulatory compliance through the development, deployment, and monitoring of analytical tools. Examples include Fair Lending monitoring, FDIC, and compliance with CECL and IFRS standards in TMCC's critical accounting estimates.

What you bring

  • Graduate degree in Data Science or a closely related field of study.

  • Executive technical leadership:15+ years of relevant professional experience in data science, machine learning, or applied analytics, including substantial hands-on ownership of analytical model development and production machine learning systems.

  • Demonstrated success in applying predictive, prescriptive, forecasting, simulation, optimization, and related methods to complex business problems across multiple domains.

  • Financial services and regulated environment experience:Significant experience in financial services, including work in regulated decisioning environments and model-driven processes with governance, auditability, and financial or regulatory impact.

  • People leadership: people-management experience, including leadership of technical organizations, leadership of managers of managers, coaching senior leaders, and direct management of senior individual contributors. Proven ability to build high-performing teams, strengthen leadership capability, and create environments in which technical talent thrives.

  • Production machine learning lifecycle ownership:Demonstrated experience building, deploying, and operating machine learning or optimization systems in production, with accountability across the full lifecycle from design and development through deployment, monitoring, drift management, and retraining in the cloud.

  • Programming, cloud, and data platform proficiency:Strong proficiency in Python and SQL, along with hands-on experience with tools such as R or SAS, cloud platforms such as AWS, GCP, or Azure, and modern data technologies such as Snowflake, Spark, or Databricks.

  • Executive presence and enterprise influence:Proven ability to shape strategy, lead cross-functional prioritization, and translate complex analytical concepts and technical tradeoffs into clear recommendations for executives and senior business leaders.

  • Governance mindset:Strong instinct for ensuring that analytical decisions can be demonstrated to be correct, reproducible, explainable, and defensible before deployment in production.

What We'll Bring

During your interview process, our team can fill you in on all the details of our industry-leading benefits and career development opportunities. A few highlights include:

  • A work environment built on teamwork, flexibility, and respect

  • Professional growth and development programs to help advance your career, as well as tuition reimbursement

  • Team Member Vehicle Purchase Discount

  • Toyota Team Member Lease Vehicle Program (if applicable)

  • Comprehensive health care and wellness plans for your entire family

  • Toyota 401(k) Savings Plan featuring a company match, as well as an annual retirement contribution from Toyota regardless of whether you contribute (if applicable)

  • Paid holidays and paid time off

  • Referral services related to prenatal services, adoption, childcare, schools and more

  • Tax Advantaged Accounts (Health Savings Account, Health Care FSA, Dependent Care FSA)

  • Relocation assistance (if applicable)


Belonging at Toyota


Our success begins and ends with our people. We embrace all perspectives and value unique human experiences. Respect for all is our North Star.


Applicants for our positions are considered without regard to race, ethnicity, national origin, sex, sexual orientation, gender identity or expression, age, disability, religion, military or veteran status, or any other characteristics protected by law.


Have a question, need assistance with your application or do you require any special accommodations? Please send an email to talent.acquisition@toyota.com.


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