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Opt Cpt Data Analyst Jobs in Minnesota (NOW HIRING)

Sr Business Analyst

Minneapolis, MN · On-site

$81K - $102K/yr

Use data from a variety of sources to analyze complex business issues, incorporating company and ... CPT, F-1 OPT, TN). In-Office Collaboration We are a client-centric, relationship-based business.

Intern Finance

Mankato, MN · On-site

$17.50 - $23/hr

CPT & Pre-Opt candidates invited to apply. This is a paid internship; however, the intern must ... Support daily pricing processes through data review, analysis, and reporting. * Assist in reviewing ...

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Opt Cpt Data Analyst information

What is an Opt CPT Data Analyst?

An Opt CPT Data Analyst is a professional who specializes in analyzing data related to Optional Practical Training (OPT) and Curricular Practical Training (CPT) programs for international students in the United States. They collect, process, and interpret large datasets to help educational institutions or employers understand trends, compliance, and outcomes associated with OPT and CPT participation. Their work often involves ensuring visa regulations are followed and providing actionable insights to improve program effectiveness. Strong analytical, technical, and communication skills are essential in this role. This position may also require familiarity with immigration policies and student information systems.

What are the key skills and qualifications needed to thrive as an Opt CPT Data Analyst?

To thrive as an Opt CPT Data Analyst, you need strong analytical skills, proficiency in data interpretation, and a relevant degree in statistics, mathematics, computer science, or a related field. Familiarity with data analysis tools such as SQL, Excel, Python, or specialized healthcare analytics platforms, along with knowledge of CPT (Current Procedural Terminology) coding, is typically required. Attention to detail, critical thinking, and effective communication skills set outstanding analysts apart. These capabilities are essential to accurately interpret complex datasets, ensure data integrity, and support data-driven decision-making in healthcare operations.

How does an Opt CPT Data Analyst typically collaborate with cross-functional teams to ensure data accuracy and compliance?

An Opt CPT Data Analyst frequently works alongside teams such as compliance, IT, billing, and clinical staff to validate data accuracy and ensure adherence to healthcare regulations. This role requires clear communication to interpret complex data sets, resolve discrepancies, and implement effective data management processes. Regular meetings and collaborative problem-solving are common, as the analyst must often translate technical findings into actionable insights for non-technical stakeholders. This teamwork is essential to maintain compliance with standards like HIPAA and to optimize billing and reporting workflows.

What is the difference between Opt Cpt Data Analyst vs Opt Cpt Data Scientist?

AspectOpt Cpt Data AnalystOpt Cpt Data Scientist
Required CredentialsBachelor's in Data Analysis, Statistics, or related field; often certifications like Microsoft Excel or TableauBachelor's or Master's in Data Science, Computer Science, or related; certifications like Python, R, or machine learning
Work EnvironmentBusiness settings, finance, healthcare, retailTech firms, research institutions, large enterprises
Employer & Industry UsageCommon in industries requiring data reporting and visualizationFocused on predictive modeling, advanced analytics, and AI

Opt Cpt Data Analysts primarily handle data collection, cleaning, and reporting to support business decisions. In contrast, Opt Cpt Data Scientists develop models and algorithms to extract deeper insights. Both roles require strong analytical skills, but Data Scientists typically have more advanced technical expertise and education.

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Infographic showing various Opt Cpt Data Analyst job openings in Minnesota as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 14% Part Time, and 3% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.

Senior Data Scientist - Clinical Informatics (Analytics Enablement)

Hispanic Alliance for Career Enhancement

Virginia, MN • On-site

$83.43 - $222.48/hr

Other

Medical, Dental, Vision, Retirement, PTO

Re-posted yesterday


Key responsibilities

  • Serve as a subject matter expert in clinical data and structure and apply this data to solve healthcare problems.

  • Design, maintain, and document clinical data models, taxonomies, and classification frameworks to enable consistent data interpretation.

  • Build and maintain clinical data assets, including feature stores, data documentation, and data quality frameworks, to support analytics, reporting, and AI/ML use cases.


Job description

We're building a world of health around every individual—shaping a more connected, convenient, and compassionate health experience. At CVS Health®, you’ll be surrounded by passionate colleagues who care deeply, innovate with purpose, hold ourselves accountable, and prioritize safety and quality in everything we do. Join us and be part of something bigger—helping to simplify health care one person, one family, and one community at a time.

Position Summary

CVS Health’s Analytics & Behavior Change (A&BC) team is an organization working to solve some of the most challenging problems at the intersection of technology and healthcare. A&BC leverages advanced analytics, clinical informatics, and hypothesis‑driven approaches to transform data into actionable, customer‑centric insights that drive growth, improve health outcomes, and expand access to healthcare across all CVS Health businesses. Our teams build next‑generation data and AI products that help power CVS Health to make healthier happen for 100+ million customers.

Responsibilities
  • Serve as a subject matter expert in clinical data, including CCD data, claims, pharmacy, lab results, and clinical documentation, with deep understanding of how to structure and apply this data to solve healthcare problems.
  • Design and maintain clinical data models, taxonomies, and classification frameworks that enable consistent interpretation and use of clinical data across the organization.
  • Build the clinical data feature store, establishing standards, documentation, and best practices that accelerate adoption of clinical data for downstream analytics, reporting, and AI/ML use cases.
  • Develop analytics by building well‑documented, validated, and reusable data assets (tables, views, features) that empower analysts and data scientists to work independently with clinical data.
  • Create and maintain comprehensive data documentation, including data dictionaries, lineage, business logic, known limitations, and appropriate use guidelines for clinical datasets.
  • Build queries, dashboards, and data visualizations to effectively communicate data quality metrics, data availability, and clinical insights to technical and non‑technical stakeholders.
  • Partner with clinical, operational, and business stakeholders to understand their data needs, translate requirements into data solutions, and ensure clinical data assets meet their analytical objectives.
  • Maintain data quality frameworks for clinical data, including validation rules, anomaly detection, and monitoring processes to ensure data integrity and reliability.
  • Translate clinical concepts into analytical frameworks, ensuring that business partners understand the capabilities and limitations of available clinical data.
  • Collaborate with data engineering teams to inform data pipeline development, ensuring clinical data is ingested, transformed, and stored in ways that support downstream analytics needs.
  • Contribute to data governance initiatives, including compliance with HIPAA, data privacy regulations, and internal data stewardship policies.
  • Develop and deliver training, presentations, and consultations to existing and prospective data consumers on clinical data assets, appropriate use, and analytics opportunities.
  • Stay current with clinical data standards (HL7, FHIR, ICD‑10, SNOMED‑CT, LOINC, CPT, NDC, RxNorm) and industry best practices in clinical informatics.
Required Qualifications
  • 4+ years of relevant experience in clinical informatics, healthcare analytics, or clinical data management.
  • Expertise in clinical data types and structures, including CCD data, lab results, clinical notes, and administrative healthcare data.
  • Strong knowledge of clinical coding systems and terminologies, such as ICD‑10, CPT, HCPCS, SNOMED‑CT, LOINC, NDC, and RxNorm.
  • Experience designing and documenting data models, taxonomies, or classification frameworks for clinical or healthcare data.
  • Proven ability to enable and support downstream data consumers (analysts, data scientists, business users) through documentation, training, and consultative support.
  • Proficiency with SQL and experience working with large‑scale healthcare datasets.
  • Experience using cloud‑based data platforms, preferably Google Cloud Platform (GCP) tools including BigQuery, for querying, transforming, and managing data.
  • Strong understanding of data quality principles, including validation, profiling, and monitoring of healthcare data.
  • Excellent written and verbal communication skills, including the ability to explain complex clinical data concepts to both technical and non‑technical audiences.
Preferred Qualifications
  • Proven experience integrating clinical (CCD/OMOP/FHIR) and administrative (claims) data into unified, patient‑centric data models, with deep understanding of the strengths, limitations, and complementary nature of each data type.
  • Experience with patient data normalization & standardization for patient attributes and cross‑source harmonization.
  • Hands‑on experience reconciling clinical and claims data, including diagnosis alignment, medication reconciliation (prescribed vs. dispensed), and encounter/visit matching.
  • Experience integrating third‑party and enrichment data sources, including SDOH indices (ADI, SVI), consumer/demographic data, mortality data, and provider reference data into patient‑level datasets.
  • Expert knowledge of clinical and administrative coding systems, including ICD‑10‑CM/PCS, CPT/HCPCS, SNOMED‑CT, RxNorm, NDC, LOINC, and NPI.
  • Experience with classification and grouping systems such as HCC, CCS, DRG, and therapeutic class hierarchies.
  • Experience designing patient‑centric data models, feature stores, and dashboards that aggregate longitudinal data across sources, including demographics, encounters, conditions, medications, labs, utilization, cost, and enrichment attributes.
  • Proven ability to enable downstream data consumers through analytics and well‑documented, validated, and reusable data assets, with experience creating data dictionaries, lineage documentation, and self‑service analytics layers.
  • Understanding of healthcare business contexts such as care management, value‑based care, quality measurement (HEDIS, Stars), and population health.
Education
  • Bachelor’s degree in health informatics, Public Health, Nursing, Health Information Management, Computer Science, Statistics, or a related quantitative or clinical field or an equivalent combination of formal education and experience.
  • Master’s degree or higher in Health Informatics, Biomedical Informatics, Clinical Informatics, Public Health, Epidemiology, or a related field is strongly preferred.
  • Clinical background (RN, PharmD, MD, or similar) with transition into informatics/analytics is highly valued.
Job Details

Anticipated Weekly Hours: 40

Time Type: Full time

Pay Range: $83,430.00 – $222,480.00 (base hourly rate or base annual full‑time salary)

Benefits

Our people fuel our future. Our teams reflect the customers, patients, members and communities we serve and we are committed to fostering a workplace where every colleague feels valued and that they belong. This full‑time position is eligible for a comprehensive benefits package designed to support the physical, emotional, and financial well‑being of colleagues and their families. The benefits include medical, dental, and vision coverage, paid time off, retirement savings options, wellness programs, and other resources, based on eligibility. Additional details about available benefits are provided during the application process and on Benefits Moments.

We anticipate the application window for this opening will close on: 10/02/2026.

Qualified applicants with arrest or conviction records will be considered for employment in accordance with all federal, state and local laws.

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