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Data Science Analyst Intern Jobs (NOW HIRING)

Quadax, an award-winning leader in healthcare revenue cycle technology, is seeking a Data Science Analyst to join our Team and help us create the best Revenue Cycle Optimization solution in the ...

Responsibilities Data Scientists at Mayo Clinic perform detailed analysis of large bodies of heterogeneous data in order to discover new patterns and insights having an impact upon patient health and ...

Data Scientists at Mayo Clinic perform detailed analysis of large bodies of heterogeneous data in order to discover new patterns and insights having an impact upon patient health and augmenting human ...

Data Scientists at Mayo Clinic perform detailed analysis of large bodies of heterogeneous data in order to discover new patterns and insights having an impact upon patient health and augmenting human ...

Launch your data science or technical analyst career by building AI and analytics solutions that help Caterpillar customers manage fleets, predict equipment failures, and optimize operations around ...

The Data Science Analyst assists in the preparation, design and execution of models and data products to improve the academic and business outcomes of Stride. The position participates as a member of ...

As a Data Analyst Intern, you will have the opportunity to work closely with our dedicated team ... Pursuing a degree in Data Science, Statistics, Computer Science, or a related field * Relevant ...

Job Overview The Program Data Science Analyst will play a critical role in supporting program and project planning, execution, and monitoring activities across various initiatives. This role blends ...

Job Overview The Program Data Science Analyst will play a critical role in supporting program and project planning, execution, and monitoring activities across various initiatives. This role blends ...

Associate Data Scientist

Sunnyvale, CA · On-site +1

$174K - $202K/yr

... Science, Data Analytics Engineering, Data Science, Statistics, or related quantitative field (or foreign equivalent). 1 year of experience in the job offered, as a Data Analytics Engineer Intern ...

Job Overview The Program Data Science Analyst will play a critical role in supporting program and project planning, execution, and monitoring activities across various initiatives. This role blends ...

Required : • Bachelor's degree in Engineering, Computer Science, Economics, Statistics, Mathematics, or another quantitative field • 8+ years of experience in data science, analytics, or a ...

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Data Science Analyst Intern information

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How much do data science analyst intern jobs pay per hour?

As of Jul 12, 2026, the average hourly pay for data science analyst intern in the United States is $22.50, according to ZipRecruiter salary data. Most workers in this role earn between $17.31 and $24.52 per hour, depending on experience, location, and employer.

What does a Data Science Analyst Intern do?

A Data Science Analyst Intern assists with analyzing large datasets to uncover patterns, trends, and insights that support business decisions. They typically work alongside data scientists and analysts to clean, organize, and visualize data, as well as help build and test predictive models. Interns may also assist in preparing reports and presentations that communicate findings to stakeholders. This role provides hands-on experience with data analysis tools and techniques, and is a valuable stepping stone for a career in data science.

What are some typical projects or tasks that a Data Science Analyst Intern might work on during their internship?

As a Data Science Analyst Intern, you can expect to work on projects such as cleaning and analyzing large datasets, building and testing predictive models, and creating visualizations to communicate findings to stakeholders. Interns often collaborate closely with data scientists, engineers, and business analysts, gaining exposure to real-world data challenges and learning how to apply statistical and machine learning techniques. The role usually involves using tools like Python, R, and SQL, and you may also have opportunities to present your work to different teams, helping you develop both technical and communication skills.

What are the key skills and qualifications needed to thrive as a Data Science Analyst Intern, and why are they important?

To thrive as a Data Science Analyst Intern, you need a solid grasp of statistics, data analysis, and programming languages such as Python or R, typically supported by coursework or a degree in a quantitative field. Familiarity with data visualization tools like Tableau, SQL databases, and version control systems (e.g., Git) is often required. Problem-solving ability, attention to detail, and strong communication skills help interns effectively interpret data and share insights with team members. These skills are crucial for transforming raw data into actionable business insights and supporting data-driven decision-making.

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

AspectData Science Analyst InternData Analyst Intern
Required SkillsBasic programming, statistical analysis, data visualizationData manipulation, Excel, basic SQL
Work EnvironmentTech companies, startups, research labsBusiness, finance, marketing sectors
Typical Duration3-6 months internship3-6 months internship

The Data Science Analyst Intern role focuses on applying statistical and programming skills to analyze complex data sets, often involving machine learning and predictive modeling. In contrast, Data Analyst Interns primarily handle data cleaning, reporting, and visualization to support business decisions. Both roles are entry-level, require similar foundational skills, and are common in tech and business industries. Understanding these differences helps candidates target their applications effectively.

More about Data Science Analyst Intern jobs
What cities are hiring for Data Science Analyst Intern jobs? Cities with the most Data Science Analyst Intern job openings:
What are the most commonly searched types of Data Science Analyst jobs? The most popular types of Data Science Analyst jobs are:
What states have the most Data Science Analyst Intern jobs? States with the most job openings for Data Science Analyst Intern jobs include:
Infographic showing various Data Science Analyst Intern job openings in the United States as of July 2026, with employment types broken down into 1% Locum Tenens, 1% Internship, 86% Full Time, 6% Part Time, 1% Temporary, and 5% Contract. Highlights an 82% Physical, 5% Hybrid, and 13% Remote job distribution, with an average salary of $46,809 per year, or $22.5 per hour.
Senior Data Science Analyst

Senior Data Science Analyst

University of Texas at Austin

Austin, TX • On-site

$85K - $107K/yr

Other

Posted 6 days ago


University Of Texas at Austin rating

8.1

Company rating: 8.1 out of 10

Based on 62 frontline employees who took The Breakroom Quiz

134th of 552 rated colleges and universities


Job description

Job Posting Title:

Senior Data Science Analyst

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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:

AUSTIN, TX

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Job Details:

Purpose

The Senior Data Science Analyst is a senior-level expert responsible for leading enterprise-wide data science initiatives that advance clinical care, operational efficiency, and innovation. Reporting to the Chief Data Officer (CDO) or other departmental leader, this role designs and deploys complex statistical and machine learning models, oversees data architecture improvements, and serves as a trusted advisor to organizational leadership. The Senior Data Science Analyst mentors data science staff, guides strategic analytics decisions, and leads the development of advanced data capabilities across the institution.

Responsibilities

Strategic Data Science and Advanced Modeling

  • Leads the development of advanced ML and AI models, including deep learning and natural language processing.

  • Oversees the design of analytical frameworks for organization-wide initiatives.

  • Interprets findings for executive and governance audiences.

  • Implements scalable model architectures and optimization strategies.

  • Advises leadership on risks, opportunities, and emerging technologies.

Data Architecture, Integration, and Standards

  • Leads the integration of heterogeneous data sources across the enterprise.

  • Designs data architectures supporting advanced modeling and analytics.

  • Develops and enforces data standards, quality measures, and governance.

  • Creates robust data models for research, predictive analytics, and operational use.

  • Partners with IT to optimize cloud infrastructure and MLOps solutions.

Data Visualization

  • Creates enterprise-level dashboards, scorecards, and reporting methodologies.

  • Standardizes KPIs across clinical and operational domains.

  • Leads automation of recurring analytics and model-driven insights.

Stakeholder Leadership and Strategic Consultation

  • Advises senior executives, clinical leaders, and program directors.

  • Leads requirements workshops and data strategy sessions.

  • Builds consensus on model adoption, data definitions, and governance.

  • Represents the analytics program at committees and external forums.

Mentorship, Innovation, and Documentation

  • Mentors junior and intermediate analysts in advanced analytics techniques.

  • Documents analytical frameworks, data sources, and methodological decisions.

  • Leads pilots of emerging AI/ML tools, including synthetic data and automation.

  • Contributes to research collaborations, publications, and scholarly activity.

MARGINAL OR PERIODIC FUNCTIONS:

  • Conducts periodic audits of data quality and governance standards.

  • Evaluates emerging AI/ML tools through short pilots and reports findings.

  • Facilitates executive briefings on strategic analytics initiatives.

  • Adheres to internal controls and reporting structure.

  • Performs related duties as required.

KNOWLEDGE/SKILLS/ABILITIES

Strategic Decision Making and Agility

  • Demonstrates strong strategic thinking and has the ability to navigate ambiguous environments.

  • Connects analytics roadmap to institutional goals and future capabilities.

  • Frames enterprise analytics choices with clear criteria and risk/benefit analysis.

Functional/Technical Skills

  • Exhibits expertise in ML, AI, and advanced statistical modeling.

  • Selects and implements appropriate ML architectures aligned to problem constraints.

  • Designs robust data models and pipelines with reproducibility and monitoring.

Problem Solving

  • Maintains a continuous learning and innovation mindset.

  • Triages model performance anomalies with root cause analysis and corrective actions.

  • Integrates different data sources to address complex, multi factor questions.

Organizational Savvy

  • Provides leadership in cross-functional teams and enterprise initiatives.

  • Builds cross functional alignment on definitions and KPIs.

  • Navigates governance bodies to advance responsible AI/ML adoption.

Executive Communication

  • Communicates at a high level with messaging tailored to executive audiences.

  • Crafts executive level narratives linking insights to operational decisions.

  • Builds dashboards and scorecards that reveal trends and actionable thresholds.

Required Qualifications

Requires a Master's Degree in Data Science, Engineering, Statistics, Computer Science, or a related analytical/quantitative field with at least 5 year(s) of experience in advanced analytics or data science.

  • Expertise in cloud analytics environments and ML frameworks.

  • Experience with healthcare data standards (OMOP, FHIR, DICOM).

  • Skilled in large-scale data processing, modeling, and architecture design.

Preferred Qualifications

Doctorate in Engineering, Mathematics, Computer Science, Health Science, Data Science, Statistics, or a related analytical/quantitative field with at least 3 year(s) of experience in a complex healthcare setting.

  • Published research or presentations at professional conferences.

  • Demonstrated experience in ETL, automation, and at least one cloud environment.

  • Experience with clinical informatics data exchange standards and platforms is also desirable.

Relevant education and experience may be substituted as appropriate.

Salary Range

$101,500+ depending on qualifications

Working Environment/Equipment
  • 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 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 questionspresented to upload any additional Required Materials (letter of interest, references, etc.) that were noted above.

Importantfor 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 thatALLRequired Materials have been uploaded. Once your job application has been submitted, you cannot make changes.

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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.

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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.

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Background Checks:

A criminal history background check will be required for finalist(s) under consideration for this position.

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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.

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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.

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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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