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Remote Data Science Jobs in Texas (NOW HIRING)

Software Engineer in Data Science

Houston, TX · On-site +1

$109K - $131K/yr

Act as a local champion for data science and AI, helping users adopt tools and articulate their changes and requirements to the wider team. The individual will work both with our data scientists and ...

Data Scientist

Austin, TX · On-site +1

MA or PhD degree in Computer Science, Engineering or other relevant area; graduate degree in Data Science or other quantitative field is preferred * Must be a U.S. Citizen

Software Engineer in Data Science

Houston, TX · On-site +1

$109K - $131K/yr

Act as a local champion for data science and AI, helping users adopt tools and articulate their changes and requirements to the wider team. The individual will work both with our data scientists and ...

Data Science Structured Data / Text Data (NLP & GenAI) About the Role We are seeking a highly skilled Data Scientist (37 years of experience) to join our team and work across two major data science ...

Data Scientist Remote [within the US] ABOUT THE ROLE: We're looking for a Data Scientist to join our Data Sciences and ML Engineering team. You'll be building, shipping, and improving the models and ...

AI and Data Science Engineer III

Houston, TX · On-site +1

$109K - $131K/yr

AI and Data Science Engineer III Position Summary Our Deloitte Human Capital team transforms technology platforms, drives innovation, and helps make a significant impact on our clients' success. We ...

AI and Data Science Engineer III

Austin, TX · On-site +1

$113K - $136K/yr

AI and Data Science Engineer III Position Summary Our Deloitte Human Capital team transforms technology platforms, drives innovation, and helps make a significant impact on our clients' success. We ...

AI and Data Science Engineer III

San Antonio, TX · On-site +1

$103K - $124K/yr

AI and Data Science Engineer III Position Summary Our Deloitte Human Capital team transforms technology platforms, drives innovation, and helps make a significant impact on our clients' success. We ...

About this role In Gartner's Services Data Science team, we innovate the way our team helps clients ... Assistance@gartner.com #LI-Remote #LI-GV1 Who are we? At Gartner, Inc. (NYSE:IT), we guide the ...

Contribute to the growth of Parkhill's data science capabilities. * Stay current with emerging trends in AI, machine learning, and data science applicable to the AEC and consulting sectors.

USAA roles may offer remote or hybrid flexibility for active-duty military spouses consistent with ... Requirements: Will accept a Bachelor's degree in Mathematics, Computer Science, Statistics ...

Contribute to the growth of Parkhill's data science capabilities. * Stay current with emerging trends in AI, machine learning, and data science applicable to the AEC and consulting sectors.

AI and Data Science Engineer III

Dallas, TX · On-site +1

$113K - $136K/yr

AI and Data Science Engineer III Position Summary Our Deloitte Human Capital team transforms technology platforms, drives innovation, and helps make a significant impact on our clients' success. We ...

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Remote Data Science information

See Texas salary details

$20.7K

$91.9K

$175.4K

How much do remote data science jobs pay per year?

As of Jun 12, 2026, the average yearly pay for remote data science in Texas is $91,936.00, according to ZipRecruiter salary data. Most workers in this role earn between $47,489.00 and $127,517.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Remote Data Scientist, and why are they important?

To thrive as a Remote Data Scientist, you need strong analytical skills, proficiency in statistics, and a solid background in mathematics or computer science, often supported by a relevant degree. Expertise in programming languages such as Python or R, familiarity with machine learning libraries, and experience with cloud-based data platforms are typically required. Excellent communication, self-motivation, and time management skills help you effectively collaborate and deliver results in a remote environment. These skills ensure accurate data analysis, meaningful insights, and successful teamwork despite physical distance.

How do remote data scientists typically collaborate with cross-functional teams to deliver insights?

Remote data scientists often work closely with product managers, engineers, and business analysts using digital collaboration tools such as Slack, Zoom, and project management platforms. Regular virtual meetings, code sharing via Git repositories, and clear documentation are essential to ensure alignment and transparency. While working remotely can present challenges in communication, proactive updates and scheduled syncs help foster strong teamwork and keep projects on track.

What is remote data science?

Remote data science refers to the practice of performing data analysis, modeling, and interpretation tasks from a location outside of a traditional office, such as from home or a co-working space. Remote data scientists use tools like Python, R, and SQL to analyze data, build predictive models, and communicate insights to stakeholders, all while collaborating virtually with their teams. This setup offers flexibility and can increase access to global job opportunities, but also requires strong self-motivation and communication skills to be effective.

Can a data scientist work fully remote?

Yes, many data scientists work fully remote, especially in companies that prioritize flexible work arrangements. Remote data science roles often require strong communication skills, proficiency with collaboration tools, and the ability to work independently on projects using programming languages like Python or R. However, some positions may require occasional in-person meetings or on-site presence depending on company policies.

Is 40 too late for data science?

Age is not a barrier to entering data science, and many professionals start or transition into the field later in life. Success depends on acquiring relevant skills such as programming, statistics, and machine learning, often through online courses or certifications, regardless of age.

Will AI replace data scientists?

AI is transforming the role of data scientists by automating routine tasks such as data cleaning and basic analysis, but it does not eliminate the need for human expertise in interpreting results, designing models, and making strategic decisions. Data scientists will continue to be essential for developing complex algorithms, understanding business context, and ensuring ethical use of AI tools. Skills in programming, statistical analysis, and machine learning remain critical for the profession's evolving landscape.

What Are the Qualifications to Get a Remote Data Science Job?

The qualifications for a remote data scientist depend in large part on your employer and their industry. Most employers expect remote data science professionals to have at least a bachelor’s degree in statistics, math, computer science, or a related field. Some expect postgraduate degrees in a field like data mining or machine learning or demonstrable skills in these areas. As a remote worker, you need access to relevant programs and an internet connection. You may also want to pursue certification, such as becoming a Certified Analytics Professional (CAP).

What is the difference between Remote Data Science vs Remote Data Analyst?

AspectRemote Data ScienceRemote Data Analyst
Required CredentialsDegree in Data Science, Statistics, or related field; programming skills in Python/R; knowledge of machine learningDegree in Statistics, Mathematics, or related field; proficiency in Excel, SQL, and data visualization tools
Work EnvironmentCollaborative teams, research-focused, often involves building models and algorithmsData reporting, visualization, and interpreting data trends for decision-making
Employer & Industry UsageTech companies, finance, healthcare, e-commerceMarketing agencies, retail, finance, healthcare

Remote Data Science involves developing predictive models and advanced analytics, requiring programming and machine learning skills. Remote Data Analysts focus on interpreting data, creating reports, and visualizations. While both roles analyze data remotely, Data Scientists typically handle more complex modeling tasks, whereas Data Analysts focus on data interpretation and reporting.

What is the 80 20 rule in data science?

In data science, the 80/20 rule, also known as the Pareto principle, suggests that roughly 80% of results come from 20% of the efforts or features. Data scientists often use this concept to focus on the most impactful variables, optimize models, and prioritize tasks for efficiency.
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 Remote Data Science jobs? Cities in Texas with the most Remote Data Science job openings:

Software Engineer in Data Science

Vitol

Houston, TX • On-site, Remote

$109K - $131K/yr

Full-time

Posted 14 days ago


Job description

Company Description

Vitol is the world's largest independent energy and commodities trading company. Every day we use our expertise and logistical networks to distribute energy around the world, efficiently and responsibly. From 40 offices worldwide, we seek to add value across the energy supply chain, including deploying our scale and market understanding to help facilitate the energy transition. To date, we have committed over $1 billion of capital to renewable projects and are identifying and developing low-carbon opportunities around the world.

Our people are our business. Talent is precious to us and we create an environment in which individuals can reach their full potential, unhindered by hierarchy. Our team comprises more than 65+ nationalities and we are committed to developing and sustaining a diverse work force. Learn more about us here.

This Role is located in Houston, TX - In office 5x a week

Job Description

As our portfolio of work continues to grow, we are looking for an experienced Software Engineer to join our global data science and machine learning team.  This role will have an initial focus on supporting our GenAI tools, including our firmwide virtual assistant.  Concretely this means you will:

  • Implement: take the requirements from our broad range of commercial stakeholders and translate these into application features.
  • Design: Ensure we design and build the models and tools to meet the functional/non-functional requirements, as well as being supportable.  The role will also help partner teams understand how they can support and integrate to the AI tools.
  • Translate: Act as a local champion for data science and AI, helping users adopt tools and articulate their changes and requirements to the wider team.

The individual will work both with our data scientists and machine learning engineers but will also need to directly engage with the commercial teams (across trading, operations, support functions, etc.).

The role will also act as a bridge between the Data Science team and other technology teams for areas like application integration, data sourcing, infrastructure and tooling.

For the successful candidate, this role will give them exposure across the machine learning lifecycle, being able to apply their skills wherever they can add value, from working with business stakeholders to help define the project, to data collation through to solution design and model implementation.

We are looking for a candidate who brings both a breadth and depth of experience, from a theoretical and practical perspective; but equally someone who can and wants to continue learning.   

As a small team, everyone is expected to organize, prioritize and execute their own tasks; with a strong focus on maximizing the business value from their actions.  This means the individual will need to be comfortable working on multiple projects simultaneously, managing competing priorities and stakeholder requirements.

The successful candidate will join a team of experienced, collaborative practitioners, who are (pragmatically) solving some of the most challenging and impactful problems the energy industry is facing; as well as pushing the boundaries around the 'art of the possible'.

Core Responsibilities include:

  • Act as the primary point of contact in Houston for our GenAI toolset
  • In conjunction with the global Data Scientists deliver models and solutions to business users, and other technology teams across a wide range of projects and technologies
  • Develop, test, maintain software tools and data pipelines for machine learning
  • Provide software engineering and design expertise and best practices (Python) with a focus on maintainability, performance, and reliability
  • As needed, take ownership of key technical infrastructure
  • Engage with projects at any point in their lifecycle, understand and debug bespoke applications; driving performance and reliability
  • Manage relationships and priorities across projects, focused on maximising value
  • Actively participating in and leading code reviews, experiment design and tooling decisions to help drive the team's velocity and quality
Qualifications

Essential Qualifications

  • 3-5+ years in industry; fluency in Python with ability to design and write clean, modular, well-documented code and a solid understanding of coding best practices
  • Master's degree in Computer Science or a related field
  • Ability and desire to learn and apply new technologies
  • Ability to logically evolve an architecture from prototype to product, considering technical debt and delivery risk
  • Collaborative approach to problem solving - ability to effectively pair program
  • Effective technical communicator - both written and verbal; able to translate loose designs into documentation / process / operating model
  • Experience with data engineering, APIs, and cloud platforms (ideally AWS) and containerization technologies (Docker)
  • Experience with enterprise software development lifecycle and tooling including continuous integration and delivery concepts/technologies 

Desired Experience

  • Experience with machine learning workflows, cloud scale machine learning infrastructure (including LLMs)
  • Experience in the energy or commodities trading industry, with knowledge of financial markets and trading concepts 
  • Data orchestrators (Airflow, Dagster) and cloud-based ETL/ELT pipelines

Personal Characteristics

  • A self-motivated individual who thrives on seeing the results of their work make an impact in the business
  • Strong communication skills, both verbally and in writing
  • Proven ability to be flexible, work hard, and a sense for the art of the possible
  • Methodical, organized and with an attention to detail - in general, in experimental design, and in code!
  • Willingness to share their knowledge and learn from others
  • An interest in learning about the commodities space
  • Resourceful, able to think creatively and adapt in a dynamic environment
  • Team player, with an open non-political style and a high level of integrity
  • Desire to be a thought-partner in a fast-growing team, and make an impact at a business that sits at the heart of the world's energy flows
Additional Information

What we offer

  • Competitive salary and benefits package
  • Large diversity of projects with real-world impacts on a truly global scale
  • Entrepreneurial environment within a flat hierarchy, where great ideas come to life quickly
  • Close collaboration with various business units across our key regions (eg. London, Singapore, Geneva)
  • A highly motivated DS and ML team comprised of experienced individuals with a supportive attitude and great team spirit
  • Being part of the energy transition through increased emphasis on renewable & alternative energy sources at a pivotal moment in the industry
  • Strong management commitment to incorporating machine learning into the future of Vitol's operations

This Role is located in Houston, TX - In office 5x a week