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Remote Data Scientist Jobs in Texas (NOW HIRING)

Bachelor's or Master's degree in Data Science, Computer Science, Engineering, Statistics, Artificial Intelligence, or related field. * 3+ years of experience in Data Science, Machine Learning, AI ...

Sr/Staff Data Scientist (Remote - US)

TX · On-site +1

$165K - $300K/yr

REMOTE Anticipated Start Date: 07/01/2026 The US base salary range for this full-time position is ... Apply data science skills to analyze large, complex datasets and identify meaningful patterns that ...

Manager, Data Scientist

Austin, TX · On-site +1

$176K - $242K/yr

Collaborate with business stakeholders, product teams, engineers, data scientists, and subject matter experts to identify high-value AI use cases and translate them into production-grade AI solutions.

Manager, Data Scientist

Austin, TX · On-site +1

$176K - $242K/yr

Collaborate with business stakeholders, product teams, engineers, data scientists, and subject matter experts to identify high-value AI use cases and translate them into production-grade AI solutions.

Senior Data Scientist, Applied ML

Austin, TX · On-site +1

$154K - $200K/yr

... for a Senior Data Scientist, Applied ML to design, build, and deploy models for critical ... In addition to our engaging workspace in South Austin, flexible and remote-friendly work options ...

Description Staff Data Scientist - Power and Renewables Why YOU want this position At Enverus,we'recommitted to empowering the global quality of life by helping our customers make energy affordable ...

Description Staff Data Scientist - Power and Renewables Why YOU want this position At Enverus, we're committed to empowering the global quality of life by helping our customers make energy affordable ...

Description Staff Data Scientist - Power and Renewables Why YOU want this position At Enverus, we're committed to empowering the global quality of life by helping our customers make energy affordable ...

Showing results 41-60

Remote Data Scientist information

See Texas salary details

$34.9K

$114.3K

$183.1K

How much do remote data scientist jobs pay per year?

As of Sep 5, 2026, the average yearly pay for remote data scientist 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 remote data scientist?

Remote data scientists are professionals who analyze and interpret complex data while working outside of a traditional office environment, typically from home or another remote location. They use statistical methods, machine learning, and programming to extract insights from data, helping organizations make data-driven decisions. Remote data scientists collaborate with teams virtually, often using tools for communication, data analysis, and project management. This flexible work arrangement allows for talent from anywhere to contribute to companies worldwide, provided they have reliable internet and the necessary technical skills.

What does a remote data scientist do?

Remote data scientists collect, confirm, and interpret data to determine useful information for their employer. Unlike in-house data scientists, remote data scientists work outside the office, either from home or another location with Wi-Fi accessibility. Remote data scientists help organizations identify patterns and trends in their data to provide information about lucrative opportunities, necessary improvements, and potential innovations. The information they get from the records they gather helps businesses make decisions in critical areas, such as product development, sales and marketing techniques, and client retention. You find remote data scientists in many different industries, including pharmaceuticals, manufacturing, and banking.

What key skills and qualifications are 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, usually demonstrated through a relevant degree. Familiarity with programming languages like Python or R, experience with machine learning frameworks, and knowledge of data visualization tools are typically required, along with certifications such as Microsoft Certified: Azure Data Scientist Associate or Google Professional Data Engineer. Excellent communication, problem-solving abilities, and self-motivation are critical soft skills for collaborating remotely and delivering insights to stakeholders. These skills are crucial for effectively analyzing data, building predictive models, and driving data-driven decisions in a distributed work environment.

How does a remote data scientist typically collaborate with team members across different time zones?

As a remote data scientist, effective collaboration across time zones often involves leveraging asynchronous communication tools like Slack, project management platforms, and version control systems such as Git. Regular virtual meetings are scheduled to accommodate overlapping hours, and clear documentation becomes crucial for keeping everyone aligned. Proactive communication, sharing progress updates, and setting clear expectations help ensure seamless teamwork despite geographical differences. This structure allows remote data scientists to contribute meaningfully while maintaining flexibility in their work schedules.

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

AspectRemote Data ScientistRemote Data Analyst
Required CredentialsDegree in Data Science, Statistics, or related field; often requires programming skills in Python or RDegree in Analytics, Business, or related field; may require proficiency in Excel, SQL, and visualization tools
Work EnvironmentResearch-focused, developing models, machine learning, and predictive analyticsData interpretation, reporting, and visualization to support business decisions
Employer & Industry UsageTech companies, finance, healthcare, and e-commerceRetail, marketing, finance, and consulting firms

Remote Data Scientists focus on building models and advanced analytics, while Remote Data Analysts interpret data and create reports. Both roles require strong analytical skills but differ in technical depth and project scope.

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

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

What cities in Texas are hiring for Remote Data Scientist jobs?

Cities in Texas with the most Remote Data Scientist job openings:

Infographic showing various Remote Data Scientist job openings in Texas as of August 2026, with employment types broken down into 85% Full Time, and 15% Part Time. Highlights an 100% Remote job distribution, with an average salary of $114,350 per year, or $55 per hour.

Senior AI Data Scientist - Solutions Developer

USAA

San Antonio, TX • On-site, Remote

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

This job post has expired 1 day ago. Applications are no longer accepted.


USAA rating

8.2

Company rating: 8.2 out of 10

Based on 265 frontline employees who took The Breakroom Quiz

53rd of 175 rated banks


Job description

Why USAA?

At USAA, our mission is to empower our members to achieve financial security through highly competitive products, exceptional service and trusted advice. We seek to be the #1 choice for the military community and their families.

Embrace a fulfilling career at USAA, where our core values – honesty, integrity, loyalty and service – define how we treat each other and our members. Be part of what truly makes us special and impactful.

We are proud to support active-duty military spouses. USAA roles may offer remote or hybrid flexibility for active-duty military spouses consistent with applicable policy and business needs.

The Opportunity

As a dedicated AI Data Solutions Scientist in the Technology organization at USAA, you will work within our innovative Data Science team and collaborate cross-functionally with our architecture, engineering, and product partners to transform our operations and experiences while producing actionable insights to drive our association forward. As a member of our dynamic community of problem-solvers, you will tackle a broad and evolving spectrum of business targets to provide outstanding impacts for our membership through scaled solutions and cloud technologies, leveraging both structured and unstructured data through traditional pillars of operations research such as simulation, optimization, and machine-learning techniques, as well as a heavy emphasis on cutting-edge technologies with generative AI, large/small language models, and advanced agent frameworks.

This team is the backbone of the next generation of AI modeling at USAA, and we hope you join us on the frontier!

We offer a flexible work environment that requires an individual to be in the office 4 days per week. This position can be based in one of the following locations: San Antonio, TX, Plano, TX, or Phoenix, AZ. Relocation assistance is not available for this position.

What you'll do:

  • Gather, interpret, and manipulate structured and unstructured data to enable advanced analytical solutions for the business.
  • Develop scalable, automated solutions using machine learning, simulation, and optimization to deliver business insights and business value.
  • Select the appropriate modeling technique and/or technology with consideration to data limitations, application, and business needs.
  • Develop and deploy models within the Model Development Control (MDC) and Model Risk Management (MRM) framework.
  • Composes, and assists peers with composing, technical documents for knowledge persistence, risk management, and technical review audiences.
  • Assess business needs to propose/recommend analytical and modeling projects to add business value.
  • Work with business and analytics leaders to prioritize analytics and modeling problems/research efforts.
  • Build and maintain a robust library of reusable, production-quality algorithms and supporting code, to ensure model development and research efforts are transparent and based on the highest quality data.
  • Translate complex business request(s) into specific analytical questions, executes on the analysis and/or modeling, and then communicates outcomes to non-technical business colleagues with focus on business action and recommendations.
  • Manage project milestones, risks, and impediments.
  • Escalates potential issues that could limit project success or implementation.
  • Develop best practices for engaging with Data Engineering and IT to deploy production-ready analytical assets consistent with modeling best practices and model risk management standards.
  • Maintain expertise and awareness of cutting-edge techniques.
  • Actively seeks opportunities and materials to learn new techniques, technologies, and methodologies.
  • Serve as a mentor to junior data scientists in modeling, analytics, and computer science tasks.
  • Participate in internal communities that drive the maintenance and transformation of data science technologies and culture.
  • Ensure risks associated with business activities are effectively identified, measured, monitored, and controlled in accordance with risk and compliance policies and procedures.

What you have:

  • Bachelor’s degree in mathematics, Computer Science, Statistics, Science, Engineering, or quantitative field; OR 4 years of relevant education and/or experience; and
  • 6+ years of experience in a predictive analytics or data analysis OR Advanced Degree (e.g., Master's, PhD) in mathematics, computer science, statistics, science and engineering, ai, or other similar quantitative discipline and 4+ years of experience in predictive analytics or data analysis.
  • 4+ years of experience in training and validating statistical, physical, machine learning, and other advanced analytics models.
  • 4+ years of experience in Python for performing statical analysis and/or building and scoring AI/ML models
  • Experience writing code that is easy to follow, well documented, and commented where necessary to explain logic (high code transparency).
  • Strong experience in querying and preprocessing data from structured and/or unstructured databases using query languages such as SQL, HQL, NoSQL, etc.
  • Demonstrated skill in performing ad-hoc analytics using descriptive, diagnostic, and inferential statistics and understanding real-world constraints such as latency, cost, and reliability in AI solution designs.
  • Ability to assess and articulate regulatory implications and expectations of distinct modeling efforts across risk stripes, including experience in the documentation and statistical validation of models for risk management.
  • Advanced experience with the concepts and technologies associated with classical supervised modeling for prediction such as linear/logistic regression, discriminant analysis, support vector machines, decision trees, forest models, etc.
  • Advanced experience with the concepts and technologies associated with unsupervised modeling such as k-means clustering, hierarchical/agglomerative clustering, neighbors algorithms, DBSCAN, etc.
  • Expertise in LLMs and agentic systems development with frameworks such as LangChain/LangGraph, AgentCore, VertexAI, MCP, or others, with proven experience including prompt engineering, tuning and post-training techniques, multi-agent systems, agent optimization and tool use, RAG and context optimization, and observability and monitoring.
  • MLOps Integration experience in facilitating engineering implementation of production scaled AI solutions in partnership with dedicated AI Engineers in cloud environments such as AWS or GCP.
  • Experience communicating analytical and modeling results to non-technical business partners with emphasis on business recommendations and actionable applications of results.
  • Experience guiding and mentoring junior technical staff in business interactions and model building.

What sets you apart:

  • Financial services, insurance, banking, or other highly regulated industry experience.
  • Experience with cloud-native application development and modernization initiatives.
  • US military experience through military service or a military spouse/domestic partner

Compensation range: The salary range for this position is: $143,320 - $273,930.

USAA does not provide visa sponsorship for this role. Please do not apply for this role if at any time (now or in the future) you will need immigration support (i.e., H-1B, TN, STEM OPT Training Plans, etc.).

Compensation: USAA has an effective process for assessing market data and establishing ranges to ensure we remain competitive. You are paid within the salary range based on your experience and market data of the position. The actual salary for this role may vary by location.

Employees may be eligible for pay incentives based on overall corporate and individual performance and at the discretion of the USAA Board of Directors.

The above description reflects the details considered necessary to describe the principal functions of the job and should not be construed as a detailed description of all the work requirements that may be performed in the job.

Benefits: At USAA our employees enjoy best-in-class benefits to support their physical, financial, and emotional wellness. These benefits include comprehensive medical, dental and vision plans, 401(k), pension, life insurance, parental benefits, adoption assistance, paid time off program with paid holidays plus 16 paid volunteer hours, and various wellness programs. Additionally, our career path planning and continuing education assists employees with their professional goals.

For more details on our outstanding benefits, visit our benefits page on USAAjobs.com.

Applications for this position are accepted on an ongoing basis, this posting will remain open until the position is filled. Thus, interested candidates are encouraged to apply the same day they view this posting.

 

USAA is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.


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