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Statistical Geneticist Jobs in Arizona (NOW HIRING)

Republic Services

Data Scientist I

Phoenix, AZ · On-site

Develops and evaluates statistical, machine learning, and AI models using appropriate performance ... genetic information, or any other characteristic protected by applicable law. For any concerns ...

Republic Services

Data Scientist I

Phoenix, AZ · On-site

Develops and evaluates statistical, machine learning, and AI models using appropriate performance ... genetic information, or any other characteristic protected by applicable law. For any concerns ...

Republic Services

Data Scientist I

Phoenix, AZ · On-site

Develops and evaluates statistical, machine learning, and AI models using appropriate performance ... genetic information, or any other characteristic protected by applicable law. For any concerns ...

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All JobsStatistical Geneticist JobsStatistical Geneticist Jobs in Arizona

Statistical Geneticist information

See Arizona salary details

$68K

$90.1K

$107.5K

How much do statistical geneticist jobs pay per year?

As of Sep 1, 2026, the average yearly pay for statistical geneticist in Arizona is $90,080.00, according to ZipRecruiter salary data. Most workers in this role earn between $73,500.00 and $106,500.00 per year, depending on experience, location, and employer.

What is a statistical geneticist?

As a statistical geneticist, your duties are to develop novel statistical methods to model and interpret the data contained in human genetic material. Your responsibilities depend on the branch of statistical genetics in which you work. Your models must be built to aid in specific types of research, such as population genetics, epidemiology, or quantitative genetics, and help other scientists analyze their experiments and results. You work closely with researchers in other fields of computational biology, such as physicians, clinicians, molecular biologists, and bioinformatics researchers.

What is a statistical geneticist?

A statistical geneticist is a scientist who uses statistical methods to study the genetic basis of traits and diseases in populations. They analyze large datasets, such as genome-wide association studies (GWAS), to identify genetic variations linked to specific health conditions or traits. Statistical geneticists often collaborate with biologists, clinicians, and data scientists to design studies, develop new methodologies, and interpret genetic data. Their work helps advance our understanding of how genes contribute to complex diseases and traits, which can inform medical research and healthcare.

What are the key skills and qualifications needed to thrive as a statistical geneticist, and why are they important?

To thrive as a Statistical Geneticist, you need a solid background in genetics, statistics, and bioinformatics, typically with a PhD in genetics, statistics, or a related field. Expertise in programming languages such as R or Python, experience with genetic analysis software (e.g., PLINK, GCTA), and familiarity with high-throughput genomic data are essential. Strong analytical thinking, problem-solving abilities, and effective communication skills set top candidates apart. These skills ensure accurate interpretation of complex genetic data, meaningful scientific discoveries, and successful collaboration within multidisciplinary research teams.

How do statistical geneticists typically collaborate with laboratory scientists and data analysts on research projects?

Statistical Geneticists often work closely with laboratory scientists to interpret experimental data and design studies that effectively capture genetic variation. They also collaborate with data analysts and bioinformaticians to manage large-scale genomic datasets, ensuring data quality and the correct application of statistical models. Effective communication between these roles is essential to translate statistical findings into biological insights, making teamwork a key part of daily responsibilities. This interdisciplinary environment provides opportunities to broaden both technical and collaborative skills.

What is the difference between Statistical Geneticist vs Bioinformatician?

AspectStatistical GeneticistBioinformatician
Required CredentialsMaster's or PhD in Genetics, Statistics, or related fieldsMaster's or PhD in Bioinformatics, Computer Science, or related fields
Work EnvironmentResearch labs, academic institutions, healthcare companiesResearch labs, biotech firms, healthcare organizations
Industry UsageGenetics research, disease association studies, personalized medicineGenomic data analysis, software development, data management

While both roles involve working with genetic data, Statistical Geneticists focus on applying statistical methods to understand genetic variations and disease associations. Bioinformaticians develop computational tools and analyze large-scale biological data. The roles often overlap but differ mainly in their core focus: statistical analysis versus computational tool development.

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Statistical Geneticist jobs near you
Infographic showing various Statistical Geneticist job openings in Arizona as of August 2026, with employment types broken down into 1% Internship, 83% Full Time, 14% Part Time, and 2% Contract. Highlights an 78% Physical, 4% Hybrid, and 18% Remote job distribution, with an average salary of $90,080 per year, or $43.3 per hour.

Research Scientist I

St Joseph Hospital & Medical Center

Phoenix, AZ

$43.10 - $64.11/hr

Full-time

Re-posted 16 days ago

Job description


Job Summary and Responsibilities

As our Research Scientist, you will leverage your deep scientific knowledge to support and facilitate the organization's research programs and projects. You are expected to apply various scientific principles to drive innovation.
Every day you will design and execute rigorous laboratory research, contributing to ongoing studies through meticulous analysis. You will also actively support manuscript preparation and participate in grant writing.
To be successful in this role, you will possess proven scientific expertise, a strong track record in experimental execution and analysis. Your ability to plan research, contribute to publications, and assist in securing funding will be paramount.

The Multimodal Imaging Genetics Lab at Barrow Neuro Analytics Center is in search of a talented and motivated computational biologist to join our dynamic team. Our lab employs cutting-edge bioinformatics and machine learning, including deep learning, to understand brain aging and secondary injury mechanisms across cerebrovascular, neurodegenerative, and traumatic brain diseases. As a Bioinformatics Staff Scientist, you will be responsible for conducting and supervising analysis of large- scale, high-dimensional biological data from biobanks and longitudinal cohorts, and developing innovative computational methods to enhance understanding of cerebrovascular and Alzheimer’s disease interactions, and drive development of mechanism-based treatments for dementia. We seek a self-driven, innovative individual with strong analytical and problem-solving abilities, and exceptional communication skills.

Responsibilities:

  • Responsible for operational oversight and implementation of funded translational research program(s) in genomics
  • Plans and executes bioinformatics analysis on high-throughput genomics (including single cell) and proteomics data, integration and analysis of multi-omics data
  • Participates in the development and application of computational algorithms and statistical models for data analysis and interpretation, and development of data analysis pipelines.
  • Develops and establishes data analysis pipelines
  • Serves as a liaison for the training of technical personnel in the translational program including post-doctoral fellows, graduate and undergraduate students
Job Requirements

Required

  • Ph.D. in Genetics, Bioinformatics, Computational Biology, Statistical Genetics, or related field
  • Demonstrated experience with GWAS data analysis, population genetics, or single-cell genomics
  • Strong understanding of complex disease genetics and population structure
  • Prior work in complex disease genetics research, including analysis of large cohorts or biobank-scale datasets

Preferred

  • Experience with pathway analysis, polygenic risk scores, or Mendelian randomization is a plus
  • Publication record in peer-reviewed journals related to human genetics or genomics
  • Proficiency in programming with R, Unix/Linux, and/or Python
  • Experience with genetic analysis tools (e.g., PLINK, GCTA, METAL)
  • Experience with high-performance computing environments
  • Working knowledge of machine learning (AI/ML) algorithms and their applications in bioinformatics
Where You'll Work

Hello humankindness: Join a Legacy of Healing at Saint Joseph’s Hospital and Medical Center (SJHMC) 

Ready to make a real difference? Join SJHMC in Phoenix AZ., a 571-bed nonprofit founded by the Sisters of Mercy over 125 years ago. We're more than a hospital; we're a global destination for life-changing care, embracing patients with humankindness.

Here, your calling will flourish. We're not just a workplace; we're a community dedicated to a mission of service.

Leaders in Specialized Care:

  • Barrow Neurological Institute (BNI): A world-renowned center for groundbreaking neurological research and innovative treatments.
  • Norton Thoracic Institute (NTI): A national leader in advanced thoracic care with pioneering surgical techniques.
  • Level I Trauma Center: One of Arizona's busiest ERs, providing immediate, comprehensive care for critically injured patients 24/7.

Why SJHMC?

  • Culture of Excellence & Well-being: We care for our people, fostering professional and personal growth.
  • Community & Collaboration: Be part of a network committed to global health and well-being.
  • Join a Legacy, Shape a Future: Over 20% of our patients travel internationally for our specialized care.

This is an invitation to join a family of dedicated professionals at the forefront of medical innovation, united by the power of humankindness.

Qualifications:

Required

  • Ph.D. in Genetics, Bioinformatics, Computational Biology, Statistical Genetics, or related field
  • Demonstrated experience with GWAS data analysis, population genetics, or single-cell genomics
  • Strong understanding of complex disease genetics and population structure
  • Prior work in complex disease genetics research, including analysis of large cohorts or biobank-scale datasets

Preferred

  • Experience with pathway analysis, polygenic risk scores, or Mendelian randomization is a plus
  • Publication record in peer-reviewed journals related to human genetics or genomics
  • Proficiency in programming with R, Unix/Linux, and/or Python
  • Experience with genetic analysis tools (e.g., PLINK, GCTA, METAL)
  • Experience with high-performance computing environments
  • Working knowledge of machine learning (AI/ML) algorithms and their applications in bioinformatics
Employment Type: Full Time

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