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Associate Data Science Analyst Jobs (NOW HIRING)

We are looking for a Data Science Analyst who can not just report on performance, but also interpret data to drive decision-making to ensure our clients turn raw data into measurable business value.

We are looking for a Data Science Analyst who can not just report on performance, but also interpret data to drive decision-making to ensure our clients turn raw data into measurable business value.

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 ...

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 ...

Senior Associate, Data Science Data is at the center of everything we do. As a startup, we ... You have the skills to retrieve, combine, and analyze data from a variety of sources and structures.

Senior Associate, Data Science Data is at the center of everything we do. As a startup, we ... You have the skills to retrieve, combine, and analyze data from a variety of sources and structures.

Senior Associate, Data Science Data is at the center of everything we do. As a startup, we ... You have the skills to retrieve, combine, and analyze data from a variety of sources and structures.

Senior Associate, Data Science Data is at the center of everything we do. As a startup, we ... You have the skills to retrieve, combine, and analyze data from a variety of sources and structures.

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 Science Analyst

Saint Louis, MO · On-site

$133K - $180K/yr

Yes We are seeking a Data Science Analyst/Engineer to join our Program working with the Data Engineering Team responsible for integrating new Data Stores and building the Metadata Application Profile ...

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Associate Data Science Analyst information

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How much do associate data science analyst jobs pay per year?

As of Aug 22, 2026, the average yearly pay for associate data science analyst in the United States is $82,640.00, according to ZipRecruiter salary data. Most workers in this role earn between $62,500.00 and $97,000.00 per year, depending on experience, location, and employer.

What does an associate data science analyst do?

An Associate Data Science Analyst is an entry-level professional who assists in collecting, analyzing, and interpreting data to help organizations make data-driven decisions. They work closely with senior data scientists and analysts, using statistical tools and programming languages like Python or R to process data, create reports, and visualize results. Their responsibilities often include cleaning and organizing data sets, performing exploratory data analysis, and supporting the development of predictive models. This role is a great way to gain hands-on experience in data science while building foundational skills for more advanced positions.

What are the key skills and qualifications needed to thrive as an associate data science analyst, and why are they important?

To thrive as an Associate Data Science Analyst, you need a solid grounding in statistics, data analysis, and programming languages such as Python or R, typically supported by a degree in a quantitative field. Familiarity with data visualization tools like Tableau, SQL databases, and potentially foundational certifications in data analytics are commonly required. Strong problem-solving, critical thinking, and effective communication skills help analysts interpret data insights and convey findings to stakeholders. These competencies are crucial for transforming raw data into actionable business intelligence and supporting data-driven decision-making.

What types of projects and datasets do associate data science analysts typically work with, and how do they contribute to larger team goals?

Associate Data Science Analysts often work on projects involving data cleaning, exploratory analysis, and basic model development using real-world datasets such as sales figures, customer behavior logs, or operational metrics. Their primary responsibility is to prepare, analyze, and visualize data to uncover insights that support business decisions. They collaborate closely with more senior data scientists, business analysts, and stakeholders to ensure that their analyses align with organizational objectives. This role provides valuable exposure to the end-to-end data science workflow and lays the foundation for advancement into more specialized or senior data science positions.

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

AspectAssociate Data Science AnalystData Analyst
Required CredentialsBachelor's degree in data-related field; some roles prefer certifications in data analysis or programmingBachelor's degree in statistics, mathematics, or related field; certifications like Microsoft Excel or SQL are common
Work EnvironmentCollaborates with data scientists and engineers; involved in data modeling and analysis tasksFocuses on data collection, cleaning, and reporting; often works with business teams
Employer & Industry UsageUsed in tech, finance, healthcare industries; entry-level role in data teamsWidely used across industries for business insights and reporting

The Associate Data Science Analyst and Data Analyst roles share similarities in educational background and industry usage. However, the Associate Data Science Analyst typically involves more technical tasks like data modeling and working closely with data science teams, whereas Data Analysts focus more on data reporting and business insights. Both roles serve as entry points into data careers but differ in technical depth and collaboration scope.

What can I do with an associate data science analyst's degree in data science?

An associate data science analyst's degree prepares individuals for entry-level roles such as data analyst, data technician, or business intelligence assistant. These roles involve collecting, cleaning, and analyzing data using tools like Excel, SQL, and basic programming languages such as Python or R. The degree provides foundational skills for working in data-driven environments and can lead to further specialization or advancement in data science careers.

What cities are hiring for Associate Data Science Analyst jobs?

Cities with the most Associate Data Science Analyst 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 Associate Data Science Analyst jobs?

States with the most job openings for Associate Data Science Analyst jobs include:

Data Science Analyst II

University of Texas

San Antonio, TX • On-site

$80 - $120/hr

Other

Posted 4 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

128th of 621 rated colleges and universities


Job description

Job Posting Title: Data Science Analyst II

Hiring Department: Dell Medical School

Position Open To: All Applicants

Weekly Scheduled Hours: 40

FLSA Status: Exempt from FLSA

Earliest Start Date: Immediately

Position Duration: Expected to Continue

Location: UT MAIN CAMPUS

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. This position is not eligible for employment 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.
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.

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]

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) and 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.

Looking for a student job? Please see the Student Employment site.

Comments and Inquiries: Email comments to hrsc@austin.utexas.edu.

For questions or concerns regarding equal opportunity only, contact Equal Opportunity Services.

Additional information for applicants can be found on the Human Resources web page: Applying for Employment.

For more job information, call the Human Resource Service Center at (512) 471-4772, or toll-free at (800) 687-4178.

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