OPT Analytics Consultant Jobs
Analytics Consultant roles qualify for OPT work authorization when the position requires applying quantitative methods, data modeling, or statistical analysis, core functions tied directly to degrees in statistics, data science, economics, or information systems. Most employers in consulting, finance, and tech actively hire OPT candidates for this title.
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Get Access To All JobsINTRODUCTION
Onsite/hybrid in Chicago
ROLE AND RESPONSIBILITIES
- Bachelor's Degree and 4+ years of experience in healthcare analytics, healthcare services, statistical analysis, data engineering, business intelligence, insurance economics, or a related field.
- 3+ years of experience designing, developing, and supporting data pipelines, data integration processes, and reporting solutions utilizing healthcare and pharmacy data.
- Strong experience with SQL, Python, Databricks, and modern data engineering frameworks for data transformation, automation, and analytics.
- Experience developing, maintaining, and optimizing ETL/ELT processes to support large-scale healthcare, claims, pharmacy, and population health datasets.
- Proficiency in data modeling, relational database design, data warehousing concepts, and creation of data marts that support reporting and analytics initiatives.
- Experience working with cloud-based data platforms and distributed computing environments to process and analyze large datasets efficiently.
- Partners with business stakeholders, analysts, and technology teams to understand data requirements and deliver scalable data solutions.
- Solves moderately complex to complex business and technical problems with a focus on data quality, performance, scalability, and reliability.
- Supports strategic initiatives through the development of trusted data assets, automated workflows, and self-service analytics capabilities.
- Participates in cross-functional project teams to deliver data solutions, enhancements, and operational improvements aligned with organizational objectives.
- Demonstrates understanding of healthcare data structures including claims, eligibility, pharmacy, provider, and population health data domains.
- Applies data governance, security, and regulatory compliance standards when managing healthcare data assets.
- Supports data framework for dashboards, ad hoc analysis, and downstream data deliveries.
- Supports with complex data inquiries and data profiling.
PREFERRED REQUIREMENTS
- Advanced SQL expertise, including complex joins, window functions, query optimization, stored procedures, and performance tuning.
- Strong experience with Databricks, Spark, Delta Lake, and distributed data processing frameworks.
- Strong Python programming skills for data engineering, automation, data quality monitoring, and analytics enablement.
- Experience building and orchestrating ETL/ELT pipelines using tools such as Databricks Workflows, Airflow, Azure Data Factory, or similar technologies.
- Experience developing scalable data lake, data warehouse, and data mart solutions that support enterprise reporting and analytics.
- Knowledge of healthcare data standards and structures, including medical claims, pharmacy claims, member eligibility, provider, and population health data.
- Experience creating and supporting semantic layers, reporting datasets, and business intelligence solutions using Power BI, Tableau, or similar platforms.
- Familiarity with CI/CD practices, source control management (Git), automated testing, and DevOps concepts for data platforms.
- Experience implementing data quality frameworks, monitoring processes, and production support practices.
NOTES
Onsite/hybrid in Chicago
This is a contract role with the possibility of conversion to full-time based on business needs and performance
VIVA is an equal opportunity employer. All qualified applicants have an equal opportunity for placement, and all employees have an equal opportunity to develop on the job. This means that VIVA will not discriminate against any employee or qualified applicant on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, disability or protected veteran status.
INTRODUCTION
Onsite/hybrid in Chicago
ROLE AND RESPONSIBILITIES
- Bachelor's Degree and 4+ years of experience in healthcare analytics, healthcare services, statistical analysis, data engineering, business intelligence, insurance economics, or a related field.
- 3+ years of experience designing, developing, and supporting data pipelines, data integration processes, and reporting solutions utilizing healthcare and pharmacy data.
- Strong experience with SQL, Python, Databricks, and modern data engineering frameworks for data transformation, automation, and analytics.
- Experience developing, maintaining, and optimizing ETL/ELT processes to support large-scale healthcare, claims, pharmacy, and population health datasets.
- Proficiency in data modeling, relational database design, data warehousing concepts, and creation of data marts that support reporting and analytics initiatives.
- Experience working with cloud-based data platforms and distributed computing environments to process and analyze large datasets efficiently.
- Partners with business stakeholders, analysts, and technology teams to understand data requirements and deliver scalable data solutions.
- Solves moderately complex to complex business and technical problems with a focus on data quality, performance, scalability, and reliability.
- Supports strategic initiatives through the development of trusted data assets, automated workflows, and self-service analytics capabilities.
- Participates in cross-functional project teams to deliver data solutions, enhancements, and operational improvements aligned with organizational objectives.
- Demonstrates understanding of healthcare data structures including claims, eligibility, pharmacy, provider, and population health data domains.
- Applies data governance, security, and regulatory compliance standards when managing healthcare data assets.
- Supports data framework for dashboards, ad hoc analysis, and downstream data deliveries.
- Supports with complex data inquiries and data profiling.
PREFERRED REQUIREMENTS
- Advanced SQL expertise, including complex joins, window functions, query optimization, stored procedures, and performance tuning.
- Strong experience with Databricks, Spark, Delta Lake, and distributed data processing frameworks.
- Strong Python programming skills for data engineering, automation, data quality monitoring, and analytics enablement.
- Experience building and orchestrating ETL/ELT pipelines using tools such as Databricks Workflows, Airflow, Azure Data Factory, or similar technologies.
- Experience developing scalable data lake, data warehouse, and data mart solutions that support enterprise reporting and analytics.
- Knowledge of healthcare data standards and structures, including medical claims, pharmacy claims, member eligibility, provider, and population health data.
- Experience creating and supporting semantic layers, reporting datasets, and business intelligence solutions using Power BI, Tableau, or similar platforms.
- Familiarity with CI/CD practices, source control management (Git), automated testing, and DevOps concepts for data platforms.
- Experience implementing data quality frameworks, monitoring processes, and production support practices.
NOTES
Onsite/hybrid in Chicago
This is a contract role with the possibility of conversion to full-time based on business needs and performance
VIVA is an equal opportunity employer. All qualified applicants have an equal opportunity for placement, and all employees have an equal opportunity to develop on the job. This means that VIVA will not discriminate against any employee or qualified applicant on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, disability or protected veteran status.
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Get Access To All JobsTips for Finding OPT Sponsorship as an Analytics Consultant
Lead with your technical stack
Analytics Consultants are evaluated on tools first. List SQL, Python, R, Tableau, or Power BI prominently on your resume. Employers scanning OPT candidates want to confirm technical fit before they consider sponsorship logistics.
Target consulting firms with established OPT pipelines
Large consulting firms like Deloitte, Accenture, and McKinsey have structured processes for OPT and H-1B visa sponsorship. These employers hire analytics roles at scale, which makes sponsorship administratively routine rather than a one-off decision.
Clarify your OPT timeline upfront
Know your OPT end date and STEM extension eligibility before interviews. Employers ask. If your degree qualifies for STEM OPT, saying so immediately extends the timeline they're evaluating and removes a common objection.
Frame deliverables in business impact, not technical output
Analytics Consultants are hired to drive decisions, not just build dashboards. Reframe resume bullet points around outcomes: revenue influenced, costs reduced, decisions enabled. This positions you as a consultant, not a technician.
Pursue roles with client-facing components
Consulting employers prioritize candidates who can present findings to stakeholders. Highlight any experience translating data into recommendations for non-technical audiences. This skill differentiates analytics candidates and justifies sponsorship investment.
Apply early in the recruiting cycle
Consulting firms recruit on structured timelines, often finalizing offers months before a start date. Applying early gives employers time to process OPT paperwork and plan for potential H-1B sponsorship without timeline pressure.
Analytics Consultant OPT: Frequently Asked Questions
Does an Analytics Consultant role qualify for OPT work authorization?
Yes, provided the position requires a direct connection to your degree field. Analytics Consultant roles typically qualify when the work involves statistical analysis, data modeling, or quantitative methods tied to degrees in statistics, economics, data science, mathematics, or information systems. If your job duties match your degree's field of study, OPT authorization applies.
Can I work as an Analytics Consultant on STEM OPT extension?
Yes, if your degree is in a STEM-designated field. Degrees in statistics, computer science, mathematics, economics, and information systems typically qualify. STEM OPT extends your work authorization by 24 months, giving you up to three years of total OPT. Your employer must also be enrolled in E-Verify to be eligible to support a STEM OPT extension.
Do Analytics Consultant employers typically sponsor H-1B visas?
Many do, particularly large consulting firms that hire analytics talent at scale. Employers who hire OPT candidates for Analytics Consultant roles often have existing H-1B sponsorship processes in place. Smaller firms may sponsor on a case-by-case basis. Searching on Migrate Mate lets you filter for employers who have a documented history of sponsoring these roles.
What degree fields support OPT authorization for Analytics Consultant roles?
The most commonly accepted fields are statistics, applied mathematics, economics, data science, computer science, information systems, and operations research. Business analytics degrees also qualify at many employers. The key is demonstrating that your degree's core curriculum directly relates to the quantitative and analytical work the role requires. A clear connection between coursework and job duties strengthens your authorization.
Can I work for a consulting firm on a client site while on OPT?
Yes, client-site work is generally permitted under OPT. The employment relationship must be with your sponsoring employer, not the client. Your job offer letter, pay stubs, and any OPT-related documentation should reflect the consulting firm as your employer of record. If your assignment changes clients or locations, notify your DSO to ensure your records stay current.