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Statistics Survival Analysis Jobs in Indiana (NOW HIRING)

$35/hr

Build and refine statistical models (e.g., propensity matching, survival analysis) under the mentorship of the RWE Research team * Shadow cross-functional team meetings to gain exposure to how RWE ...

$35/hr

Build and refine statistical models (e.g., propensity matching, survival analysis) under the mentorship of the RWE Research team * Shadow cross-functional team meetings to gain exposure to how RWE ...

$35/hr

Build and refine statistical models (e.g., propensity matching, survival analysis) under the mentorship of the RWE Research team * Shadow cross-functional team meetings to gain exposure to how RWE ...

$35/hr

Build and refine statistical models (e.g., propensity matching, survival analysis) under the mentorship of the RWE Research team * Shadow cross-functional team meetings to gain exposure to how RWE ...

$35/hr

Build and refine statistical models (e.g., propensity matching, survival analysis) under the mentorship of the RWE Research team * Shadow cross-functional team meetings to gain exposure to how RWE ...

$35/hr

Build and refine statistical models (e.g., propensity matching, survival analysis) under the mentorship of the RWE Research team * Shadow cross-functional team meetings to gain exposure to how RWE ...

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Statistics Survival Analysis information

What is statistics survival analysis?

Statistics survival analysis is a branch of statistics that focuses on analyzing the expected duration of time until one or more events happen, such as death, failure, or relapse. It is commonly used in clinical trials, reliability engineering, and social sciences to estimate survival rates and compare different groups. The analysis accounts for censored data, which occurs when the outcome event has not been observed for some subjects during the study period. Techniques like Kaplan-Meier estimates and Cox proportional hazards models are frequently used in survival analysis.

What are the key skills and qualifications needed to thrive as a professional specializing in statistics survival analysis?

To thrive in Statistics Survival Analysis, you need a strong background in statistics, mathematics, and experience with survival models, typically supported by a degree in statistics, biostatistics, or a related field. Proficiency with statistical software such as R, SAS, or Python, and familiarity with specialized packages like 'survival' or 'lifelines,' is essential. Strong analytical thinking, attention to detail, and effective communication skills make someone stand out in this role. These skills and qualities are vital for accurate data interpretation, designing robust studies, and clearly conveying findings to multidisciplinary teams.

What are some common challenges faced by professionals working in survival analysis, and how can they be addressed?

Professionals in survival analysis often encounter challenges such as handling censored data, selecting appropriate statistical models, and interpreting results for non-statistical audiences. Addressing these challenges typically involves a strong understanding of statistical theory, using specialized software (like R or SAS), and collaborating closely with domain experts to ensure contextual accuracy. Regular training, peer review, and participation in interdisciplinary teams also help to overcome technical and communication barriers, making it easier to deliver actionable insights from survival analysis projects.

What is the difference between Statistics Survival Analysis vs Data Analyst?

AspectStatistics Survival AnalysisData Analyst
Required CredentialsDegree in Statistics, Mathematics, or related field; certifications like SAS or RDegree in Data Science, Statistics, or related field; proficiency in Excel, SQL, and visualization tools
Work EnvironmentResearch settings, healthcare, insurance, academiaBusiness, finance, marketing, technology companies
Industry UsageAnalyzing time-to-event data, survival rates, hazard functionsData cleaning, reporting, trend analysis, dashboards

Statistics Survival Analysis focuses on modeling and analyzing time-to-event data, often in research or healthcare contexts. Data Analysts handle broader data tasks like cleaning, visualization, and reporting across various industries. While both roles require strong analytical skills, Survival Analysis specialists typically have advanced statistical training specific to time-dependent data, whereas Data Analysts focus on interpreting data for business insights.

What are popular job titles related to Statistics Survival Analysis jobs in Indiana?

For Statistics Survival Analysis jobs in Indiana, the most frequently searched job titles are:

What job categories do people searching Statistics Survival Analysis jobs in Indiana look for?

The top searched job categories for Statistics Survival Analysis jobs in Indiana are:

What cities in Indiana are hiring for Statistics Survival Analysis jobs?

Cities in Indiana with the most Statistics Survival Analysis job openings:

Summer 2027 Internship - RWE Data Scientist - Virtual

Stryker

South Bend, IN • On-site, Remote

$35/hr

Temporary, Internship

Posted 5 days ago


Stryker rating

8.2

Company rating: 8.2 out of 10

Based on 112 frontline employees who took The Breakroom Quiz

136th of 499 rated machine equipment manufacturers


Job description

What You Get Out of the Internship

At Stryker, we believe that developing the next generation of talent is just as important as developing life-changing medical technologies. As an intern, you won’t just observe — you’ll contribute to meaningful projects, gain exposure to leaders who will mentor you, and experience a culture of innovation and teamwork that is shaping the future of healthcare. As an intern, you will:

  • Apply classroom knowledge and gain experience in a fast-paced and growing industry setting
  • Implement new ideas, be constantly challenged, and develop your skills
  • Network with key/high-level stakeholders and leaders of the business
  • Be a part of an innovative team and culture
  • Experience documenting complex processes and presenting them in a clear format

Who We Want

Challengers. People who seek out the hard projects and work to find just the right solutions.

Teammates. Partners who listen to ideas, share thoughts and work together to move the business forward.

Charismatic networkers. Relationship-savvy people who intentionally make connections with both internal partners and external contacts.

Strategic thinkers. Interns who propose innovative ideas and consistently exceed their performance objectives.

Customer-oriented achievers. Individuals with an unparalleled work ethic and customer-focused attitude who bring value to their partnerships.

Game changers. Persistent interns who will stop at nothing to live out Stryker’s mission to make healthcare better.

Opportunities Available

As a Real-World Evidence Data Science intern at Stryker, you will:

  • Work cross functionally with different departments including Clinical Affairs, Health Economics & Outcomes Research (HEOR), Regulatory Affairs, and Marketing to support real-world evidence generation programs
  • Assist in the design and execution of observational studies using claims (e.g., Premier PINC AI, NIS) and other real-world data sources
  • Support data extraction, cleaning, and analysis of structured and unstructured healthcare data, including applying NLP techniques to unstructured billing/clinical data
  • Prepare literature review summaries and evidence syntheses to support publication and regulatory submission efforts
  • Build and refine statistical models (e.g., propensity matching, survival analysis) under the mentorship of the RWE Research team
  • Shadow cross-functional team meetings to gain exposure to how RWE informs regulatory, reimbursement, and commercial strategy

What You Need

Required:

  • Currently pursuing a Master’s degree in Biostatistics, Epidemiology, Health Services Research, Health Economics and Outcomes Research (HEOR), Health/Biomedical Informatics, Data Science, or a related quantitative field; must remain enrolled in a degree-seeking program after the internship
  • Cumulative 3.0 GPA or above (verified at time of hire)
  • Must be legally authorized to work in the U.S. and not require employment-based sponsorship now or in the future
  • Proficiency in SQL and at least one statistical/analytical programming language (Python or R)
  • Coursework or applied project experience with observational/real-world data (claims, EHR, or registry data)
  • Strong written and verbal communication skills, with proven ability to collaborate and build relationships
  • Demonstrated leadership, problem-solving, and organizational skills with the ability to manage multiple priorities
  • Proficiency in Microsoft Office (Excel, Word, PowerPoint) and eagerness to learn in a dynamic environment

Preferred:

  • Prior exposure to claims databases (Medicare, MarketScan, Premier PINC AI, Optum) or EHR data structures
  • Familiarity with causal inference methods (propensity score matching, instrumental variables) and/or survival analysis
  • Experience with NLP applied to unstructured healthcare text
  • Prior coursework, thesis, or practicum work in a medtech, pharma, or payer setting

$20 min hourly wage – $35 max hourly wage, sign-on bonus, 11 paid holidays annually, and either paid corporate housing or a living stipend, dependent upon hiring location

Stryker is a global leader in medical technologies and, together with its customers, is driven to make healthcare better. The company offers innovative products and services in MedSurg, Neurotechnology, Orthopaedics and Spine that help improve patient and healthcare outcomes. Alongside its customers around the world, Stryker impacts more than 150 million patients annually.


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