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Statistics Survival Analysis Jobs in Indiana (NOW HIRING)

micro1 AI

Director of Biostatistics

Carmel, IN · Remote

$60 - $65/hr

Solid understanding of statistical methods used in confirmatory trials, including survival analysis, mixed models, covariate adjustment, multiplicity control, and estimand and missing-data strategies ...

micro1 AI

Director of Biostatistics

Evansville, IN · Remote

$60 - $65/hr

Solid understanding of statistical methods used in confirmatory trials, including survival analysis, mixed models, covariate adjustment, multiplicity control, and estimand and missing-data strategies ...

micro1 AI

Director of Biostatistics

South Bend, IN · Remote

$60 - $65/hr

Solid understanding of statistical methods used in confirmatory trials, including survival analysis, mixed models, covariate adjustment, multiplicity control, and estimand and missing-data strategies ...

micro1 AI

Director of Biostatistics

Fort Wayne, IN · Remote

$60 - $65/hr

Solid understanding of statistical methods used in confirmatory trials, including survival analysis, mixed models, covariate adjustment, multiplicity control, and estimand and missing-data strategies ...

micro1 AI

Director of Biostatistics

Indianapolis, IN · Remote

$60 - $65/hr

Solid understanding of statistical methods used in confirmatory trials, including survival analysis, mixed models, covariate adjustment, multiplicity control, and estimand and missing-data strategies ...

micro1 AI

Director of Biostatistics

Fishers, IN · Remote

$60 - $65/hr

Solid understanding of statistical methods used in confirmatory trials, including survival analysis, mixed models, covariate adjustment, multiplicity control, and estimand and missing-data strategies ...

micro1 AI

Biostatistician

Indianapolis, IN · Remote

$60 - $65/hr

Solid understanding of statistical methods used in confirmatory trials, including survival analysis, mixed models, covariate adjustment, multiplicity control, and estimand and missing-data strategies ...

micro1 AI

Biostatistician

Evansville, IN · Remote

$60 - $65/hr

Solid understanding of statistical methods used in confirmatory trials, including survival analysis, mixed models, covariate adjustment, multiplicity control, and estimand and missing-data strategies ...

micro1 AI

Biostatistician

South Bend, IN · Remote

$60 - $65/hr

Solid understanding of statistical methods used in confirmatory trials, including survival analysis, mixed models, covariate adjustment, multiplicity control, and estimand and missing-data strategies ...

micro1 AI

Biostatistician

Carmel, IN · Remote

$60 - $65/hr

Solid understanding of statistical methods used in confirmatory trials, including survival analysis, mixed models, covariate adjustment, multiplicity control, and estimand and missing-data strategies ...

micro1 AI

Biostatistician

Fishers, IN · Remote

$60 - $65/hr

Solid understanding of statistical methods used in confirmatory trials, including survival analysis, mixed models, covariate adjustment, multiplicity control, and estimand and missing-data strategies ...

micro1 AI

Biostatistician

Fort Wayne, IN · Remote

$60 - $65/hr

Solid understanding of statistical methods used in confirmatory trials, including survival analysis, mixed models, covariate adjustment, multiplicity control, and estimand and missing-data strategies ...

USM

Data Scientist

Columbus, IN

... Survival Analysis, Text Mining, and Time Series methods. (Must have.) Intimacy dealing with data ... Education Requirements MINIMUM MSc in Statistics, Mathematics, Computer Science; PhD preferred ...

All JobsStatistics Survival Analysis JobsStatistics Survival Analysis Jobs in Indiana

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 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 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 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:

Statistics Survival Analysis jobs near you

Director of Biostatistics

micro1 AI

Carmel, IN • Remote

$60 - $65/hr

Part-time

Posted 13 days ago

Job description

Role Title: Biostatistician


Role Type: Contractor


Location: Remote


micro1 is engaging Biostatisticians to contribute their clinical statistics expertise to a dynamic customer project focused on AI-assisted clinical research. In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required — your domain knowledge is what matters.


Scope of Work

  1. Author and review evaluation tasks that require deriving, reproducing, or validating statistical outputs from clinical datasets and associated tables, figures, and listings (TFLs).
  2. Apply expert judgment to assess the correctness and consistency of reported estimates, confidence intervals, p-values, analysis populations, and missing data handling in alignment with the statistical analysis plan (SAP).
  3. Identify discrepancies between statistical outputs and their narrative descriptions in clinical study reports (CSR), including subtle errors in population definitions, censoring rules, or multiplicity handling.
  4. Establish defensible ground truth for each evaluation task, documenting the derivation process to enable independent verification.
  5. Provide structured written rationales distinguishing true statistical errors from acceptable methodological alternatives, employing clear and concise communication.
  6. Collaborate with a multidisciplinary project team, providing statistical insights and feedback as needed to refine evaluation tasks and criteria.


Preferred Qualifications

  1. 5+ years as a biostatistician supporting clinical trials at a sponsor, CRO, or academic trials unit.
  2. Hands-on experience producing or quality controlling TFLs for regulatory submissions and working directly from CDISC SDTM/ADaM datasets.
  3. Solid understanding of statistical methods used in confirmatory trials, including survival analysis, mixed models, covariate adjustment, multiplicity control, and estimand and missing-data strategies under ICH E9(R1).
  4. Proficiency in SAS and/or R, with the ability to independently reproduce analyses from written specifications.
  5. Ability to interpret SAPs and ensure reported results are consistent with pre-specified analyses.
  6. Advanced degree (MSc or PhD) in Biostatistics, Statistics, or a closely related quantitative field.
  7. Nice to have: Experience as lead statistician on pivotal/registrational studies, authoring or reviewing CSR statistical sections, oncology endpoint expertise, and exposure to AI-assisted statistical review tools.

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