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Data Science Research Jobs in Austin, TX (NOW HIRING)

The Role As a staff scientist, you will be responsible for leading one or more AI/ML and data ... S. in operations research, engineering, computer science, applied statistics, physics, or related ...

Job Title: AI Data Science Domain Expert Job Type: Contractor (Part-Time) Location: Remote Job ... Perform independent research and fact-checking to validate technical information. * Annotate data ...

Job Title: AI Data Science Domain Expert Job Type: Contractor (Part-Time) Location: Remote Job ... Perform independent research and fact-checking to validate technical information. * Annotate data ...

Job Title: AI Data Science Domain Expert Job Type: Contractor (Part-Time) Location: Remote Job ... Perform independent research and fact-checking to validate technical information. * Annotate data ...

Research and detect valuable data sources and automate collection processes * Perform preprocessing ... MA or PhD degree in Computer Science, Engineering or other relevant area; graduate degree in Data ...

Research and detect valuable data sources and automate collection processes * Perform preprocessing ... MA or PhD degree in Computer Science, Engineering or other relevant area; graduate degree in Data ...

AI Engineer, Data Science

Austin, TX · On-site

$100 - $130/hr

... new research--especially in the fast‑moving LLM space. You'll be successful if you have: * A ... in Data Science, Mathematics, Statistics, Computer Science or a related discipline * Experience ...

Principal Data Scientist

Austin, TX · On-site

$180 - $230/hr

... data science, statistical modeling, or quantitative research experience post-PhD, with increasing responsibility and complexity. * 3 years of experience in healthcare, public health, population ...

Principal Data Scientist

Austin, TX · On-site

$180 - $240/hr

... data science, statistical modeling, or quantitative research experience post-PhD, with increasing responsibility and complexity. * 3 years of experience in healthcare, public health, population ...

This role sits at the intersection of applied research, machine learning engineering, data science, and business transformation. The ideal candidate combines strong technical expertise in Large ...

Research and detect valuable data sources and automate collection processes * Perform preprocessing ... MA or PhD degree in Computer Science, Engineering or other relevant area; graduate degree in Data ...

Independent Research * Problem-Solving * Attention to Detail Preferred Qualifications * 3+ years of experience in Data Science, Machine Learning, Applied AI, Statistics, Quantitative Analytics, or ...

... data science, statistical modeling, or quantitative research experience post- PhD, with increasing responsibility and complexity. -3 years of experience in healthcare, public health, population ...

... data science, statistical modeling, or quantitative research experience post- PhD, with increasing responsibility and complexity. -3 years of experience in healthcare, public health, population ...

As a Data Scientist/Data Science Specialist for Adidev Technologies Inc., you will be enhancing and ... S. in Computer Science, Computational Physics, Operations Research, Geospatial Sciences, Remote ...

As a Data Scientist/Data Science Specialist for Adidev Technologies Inc., you will be enhancing and ... S. in Computer Science, Computational Physics, Operations Research, Geospatial Sciences, Remote ...

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Data Science Research information

See Austin, TX salary details

$37.2K

$121.7K

$194.8K

How much do data science research jobs pay per year?

As of Aug 24, 2026, the average yearly pay for data science research in Austin, TX is $121,659.00, according to ZipRecruiter salary data. Most workers in this role earn between $97,600.00 and $134,800.00 per year, depending on experience, location, and employer.

What is data science research?

Data science research involves using scientific methods, algorithms, and systems to extract knowledge and insights from structured and unstructured data. Researchers in this field work on developing new data analysis techniques, machine learning models, and data-driven solutions to solve complex problems. The work often includes designing experiments, analyzing large datasets, and publishing findings to advance the understanding of data science methodologies.

How does a data science researcher typically collaborate with other departments within an organization?

Data Science Researchers frequently work cross-functionally, collaborating with teams such as engineering, product management, and business analytics. They often translate complex research findings into actionable insights, guiding product development or business strategies. Regular meetings, joint project planning, and code reviews are common, ensuring that research outcomes align with organizational goals. Effective communication and teamwork are key to integrating advanced data solutions into real-world applications.

What are the key skills and qualifications needed to thrive as a data science researcher, and why are they important?

To thrive as a Data Science Researcher, you need strong analytical skills, expertise in statistics and machine learning, and an advanced degree in a quantitative field such as computer science, mathematics, or engineering. Proficiency with programming languages like Python or R, data visualization tools, and experience using platforms such as TensorFlow or PyTorch is typically required. Curiosity, creativity, and clear communication are essential soft skills for designing research questions, interpreting results, and sharing findings with diverse audiences. These skills and qualities are crucial for driving innovative solutions and impactful insights in data-driven environments.

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

AspectData Science ResearchData Analyst
CredentialsTypically requires advanced degrees (Master's or PhD) in Data Science, Statistics, or related fieldsOften requires a Bachelor's or Master's degree in Data Analysis, Statistics, or related areas
Work EnvironmentResearch labs, academic institutions, or R&D departments within companiesBusiness environments, corporate offices, or consulting firms
Employer & Industry UsageUniversities, research institutions, tech companies focusing on innovationRetail, finance, healthcare, and other industries focusing on data-driven decision making

Data Science Research focuses on developing new algorithms, models, and theories, often in academic or R&D settings. In contrast, Data Analysts primarily interpret existing data to generate reports and insights for business decisions. Both roles require strong analytical skills but differ in scope, goals, and work environment.

What do data science researchers do?

Data science researchers analyze large datasets to identify patterns, develop models, and generate insights that inform decision-making. They often use programming languages like Python or R, and tools such as machine learning algorithms and statistical methods. Their work typically involves experimentation, data cleaning, and collaboration with other teams to solve complex problems.

What are the most commonly searched types of Data Science Research jobs in Austin, TX?

The most popular types of Data Science Research jobs in Austin, TX are:

What job categories do people searching Data Science Research jobs in Austin, TX look for?

The top searched job categories for Data Science Research jobs in Austin, TX are:

What cities near Austin, TX are hiring for Data Science Research jobs?

Cities near Austin, TX with the most Data Science Research job openings:

Infographic showing various Data Science Research job openings in Austin, TX as of August 2026, with employment types broken down into 1% As Needed, 85% Full Time, 11% Part Time, and 3% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $121,659 per year, or $58.5 per hour.

Full-time

Re-posted 7 days ago


University Of Texas at Austin rating

8.3

Company rating: 8.3 out of 10

Based on 64 frontline employees who took The Breakroom Quiz

129th of 622 rated colleges and universities


Job description

Job Posting Title:
Data Science Analyst II
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Hiring Department:
Dell Medical School
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Position Open To:
All Applicants
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Weekly Scheduled Hours:
40
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FLSA Status:
Exempt from FLSA
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Earliest Start Date:
Immediately
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Position Duration:
Expected to Continue
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Location:
UT MAIN CAMPUS
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Job Details:
Purpose
The Data Science Analyst II partners with clinical, operational, and administrative leaders to develop advanced analytics, predictive models, and decision-support solutions that improve patient care, operational efficiency, and organizational performance.
This role translates complex healthcare and business problems into scalable data science and machine learning solutions while collaborating closely with clinicians, informaticists, data engineers, and business stakeholders. The Data Science Analyst II develops predictive models, builds automated data pipelines, and delivers actionable insights that support enterprise decision-making and clinical innovation.
Responsibilities
Clinical & Operational Partnership
  • Partner directly with clinicians, operational leaders, researchers, and administrative stakeholders to identify analytical opportunities that improve patient care and operational performance.
  • Translate complex clinical and business questions into scalable analytical solutions.
  • Present technical findings and recommendations to both technical and non-technical audiences.
  • Serve as a trusted consultant on data science, predictive analytics, and AI initiatives.

Advanced Data Science & Predictive Modeling
  • Design, develop, validate, and deploy predictive and machine learning models supporting clinical and operational initiatives.
  • Perform feature engineering, model evaluation, hyperparameter tuning, and performance monitoring.
  • Conduct forecasting, trend analysis, anomaly detection, and scenario modeling.
  • Monitor deployed models for drift and recommend improvements as data changes.
  • Translate analytical findings into actionable recommendations.

Data Integration & Engineering
  • Build and maintain automated ETL pipelines and reproducible analytical workflows.
  • Integrate structured and unstructured data from multiple enterprise healthcare systems.
  • Ensure data quality through validation, reconciliation, and testing.
  • Partner with Data Engineering and IT teams to optimize data architecture and performance.

Visualization & Decision Support
  • Develop dashboards and interactive reporting tools that support operational and clinical decision-making.
  • Automate recurring reports and analytical processes.
  • Maintain consistency of KPIs and enterprise reporting standards.
  • Create clear visualizations that simplify complex analytical findings.

Project Leadership & Collaboration
  • Lead small-to-medium analytics initiatives from planning through implementation.
  • Define project milestones, manage priorities, and communicate status updates.
  • Mentor junior analysts and promote data science best practices.
  • Collaborate closely with data architects, engineers, informaticists, and clinical leaders to ensure successful implementation.

Marginal or Periodic Functions
  • Evaluate emerging AI, machine learning, and cloud technologies for enterprise adoption.
  • Monitor model performance and coordinate remediation following data or regulatory changes.
  • Ensure compliance with HIPAA, security standards, and institutional policies.
  • Adhere to internal controls and reporting requirements.
  • Perform related duties as assigned.

Knowledge, Skills & Abilities
Technical Expertise
  • Strong understanding of predictive analytics, statistics, and machine learning techniques.
  • Proficiency in Python, SQL, and modern analytics frameworks.
  • Experience developing automated ETL pipelines and maintaining data integrity.
  • Experience working with cloud-based analytics environments.

Communication
  • Ability to communicate technical concepts to clinical, operational, and executive audiences.
  • Strong presentation and stakeholder engagement skills.
  • Ability to translate complex analytical findings into actionable recommendations.

Collaboration
  • Demonstrated ability to partner effectively with clinicians, researchers, operational leaders, and technical teams.
  • Strong business acumen with a collaborative, solution-oriented approach.
  • Ability to balance technical feasibility with operational priorities.

Required Qualifications
  • Master's degree in Data Science, Statistics, Computer Science, Engineering, Health Informatics, or a related field, with at least three (3) years of professional experience in data science, predictive analytics, machine learning, or healthcare analytics.
  • Experience applying data science and predictive analytics to solve healthcare, clinical, or business problems.
  • Strong SQL, data modeling, and Python programming skills.
  • Experience developing ETL pipelines and working with cloud platforms (Azure, AWS, or Google Cloud).
  • Experience collaborating directly with business, operational, clinical, or research stakeholders to develop analytical solutions.
  • Excellent written, verbal, and interpersonal communication skills.
  • Relevant education and experience may be substituted as appropriate.
  • Applicants must be authorized to work in the United States on a full-time basis without the need for current or future visa sponsorship.

Preferred Qualifications
  • Doctorate in Data Science, Computer Science, Engineering, Statistics, Health Informatics, or related field.
  • Five (5)+ years of applied machine learning or healthcare analytics experience.
  • Experience supporting provider organizations, academic medical centers, hospitals, or integrated health systems.
  • Experience working with provider-side healthcare data, clinical workflows, operational healthcare analytics, or population health initiatives.
  • Experience working with healthcare datasets and interoperability standards such as OMOP, FHIR, or HL7.
  • Experience operationalizing machine learning models using MLOps practices.
  • Experience developing automated ETL pipelines and cloud-native analytics solutions.

Salary
$80,000+ depending on qualifications.
Important Employment Requirement:
Applicants must be authorized to work in the United States on a full-time basis without the need for current or future visa sponsorship. This position is not eligible for employment visa sponsorship.
Working Conditions
  • Standard office equipment
  • Repetitive use of a keyboard
  • May be exposed to such occupational hazards as communicable diseases, blood borne pathogens, ionizing and non-ionizing radiation, hazardous medications and disoriented or combative patients, or others.

Required Materials
  • Resume/CV
  • 3 work references with their contact information; at least one reference should be from a supervisor
  • Letter of interest

Important for applicants who are NOT current university employees or contingent workers: You will be prompted to submit your resume the first time you apply, then you will be provided an option to upload a new Resume for subsequent applications. Any additional Required Materials (letter of interest, references, etc.) will be uploaded in the Application Questions section; you will be able to multi-select additional files. Before submitting your online job application, ensure that ALL Required Materials have been uploaded. Once your job application has been submitted, you cannot make changes.
Important for Current university employees and contingent workers: As a current university employee or contingent worker, you MUST apply within Workday by searching for Find UT Jobs. If you are a current University employee, log-in to Workday, navigate to your Worker Profile, click the Career link in the left hand navigation menu and then update the sections in your Professional Profile before you apply. This information will be pulled in to your application. The application is one page and you will be prompted to upload your resume. In addition, you must respond to the application questions presented to upload any additional Required Materials (letter of interest, references, etc.) that were noted above.
Employment Eligibility:
Regular staff who have been employed in their current position for the last six continuous months are eligible for openings being recruited for through University-Wide or Open Recruiting, to include both promotional opportunities and lateral transfers. Staff who are promotion/transfer eligible may apply for positions without supervisor approval.
Retirement Plan Eligibility:
The retirement plan for this position is Teacher Retirement System of Texas (TRS), subject to the position being at least 20 hours per week and at least 135 days in length.
Background Checks:
A criminal history background check will be required for finalist(s) under consideration for this position.
Equal Opportunity Employer:
The University of Texas at Austin, as an equal opportunity/affirmative action employer, complies with all applicable federal and state laws regarding nondiscrimination and affirmative action. The University is committed to a policy of equal opportunity for all persons and does not discriminate on the basis of race, color, national origin, age, marital status, sex, sexual orientation, gender identity, gender expression, disability, religion, or veteran status in employment, educational programs and activities, and admissions.
Pay Transparency:
The University of Texas at Austin will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. However, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by the employer, or (c) consistent with the contractor's legal duty to furnish information.
Employment Eligibility Verification:
If hired, you will be required to complete the federal Employment Eligibility Verification I-9 form. You will be required to present acceptable and original documents to prove your identity and authorization to work in the United States. Documents need to be presented no later than the third day of employment. Failure to do so will result in loss of employment at the university.
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E-Verify:
The University of Texas at Austin use E-Verify to check the work authorization of all new hires effective May 2015. The university's company ID number for purposes of E-Verify is 854197. For more information about E-Verify, please see the following:
  • E-Verify Poster (English and Spanish) [PDF]
  • Right to Work Poster (English) [PDF]
  • Right to Work Poster (Spanish) [PDF]

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Compliance:
Employees may be required to report violations of law under Title IX and the Jeanne Clery Disclosure of Campus Security Policy and Crime Statistics Act (Clery Act). If this position is identified a Campus Security Authority (Clery Act), you will be notified and provided resources for reporting. Responsible employees under Title IX are defined and outlined in HOP-3031.
The Clery Act requires all prospective employees be notified of the availability of the Annual Security and Fire Safety report. You may access the most recent report here or obtain a copy at University Compliance Services, 1616 Guadalupe Street, UTA 2.206, Austin, Texas 78701.

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