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Data Analyst Github Jobs in Arizona (NOW HIRING)

ADELANTE HEALTHCARE INC

Data Engineer

Phoenix, AZ · On-site

$108K - $130K/yr

The Data Engineer plays a critical part in delivering validated, governed, and actionable data ... GitHub Actions. * Ability to deliver trusted, analytics-ready datasets to business teams via ...

ADELANTE HEALTHCARE INC

Data Engineer

Phoenix, AZ

$108K - $130K/yr

The Data Engineer plays a critical part in delivering validated, governed, and actionable data ... GitHub Actions. * Ability to deliver trusted, analytics-ready datasets to business teams via ...

EXL Service

Principle Data Engineer

Phoenix, AZ · On-site

$113K - $136K/yr

EXLS) is a global analytics and digital solutions company that partners with clients to improve ... GitHub - branch, release, DevOps, CI/CD pipeline. * Team player, Strong communication and ...

Pursuit Aerospace

Lead Data Scientist

Prescott, AZ · On-site

Proficient in SQL, Python, ML modeling, and time-series analytics; hands-on AI-assisted coding against Snowflake tables, pipeline orchestration, GitHub for CI/CD, Azure data platform * Effective AI ...

Pursuit Aerospace

Lead Data Scientist

Prescott, AZ · On-site

$144K - $198K/yr

Proficient in SQL, Python, ML modeling, and time-series analytics; hands-on with Claude for AI-assisted coding against Snowflake tables, pipeline orchestration, GitHub for CI/CD, Azure data platform

Ultra Clean Technology

Data Scientist

Phoenix, AZ · On-site

The Data Scientist will play a crucial role in developing advanced analytics and machine learning ... development (Github Copilot or similar), as well as Agent development in Copilot studio for ...

QuantumClean

Data Scientist

Phoenix, AZ

The Data Scientist will serve as a key contributor to the company's data and analytics strategy ... development (Github Copilot or similar), as well as Agent development in Copilot studio for ...

UCT Alumni Association

Data Scientist

Phoenix, AZ · On-site

The Data Scientist will serve as a key contributor to the company's data and analytics strategy ... development (Github Copilot or similar), as well as Agent development in Copilot studio for ...

Phoenix Staff

Lead Data & AI Engineer

Phoenix, AZ · On-site +1

$50 - $60/hr

What you've got · 8+ years of experience in data engineering or analytics with at least 5 years of ... MLflow or GitHub Actions, Power BI semantic modeling, and relevant Snowflake or Microsoft ...

IntraEdge

Big Data Engineer II

Phoenix, AZ

$55.75 - $73.75/hr

Should have experience in analysis, design, development, testing, and implementation of system ... Experience with GitHub and leveraging CI/CD pipelines * Experience with NoSQL i.e., HBase ...

Forhyre

Cloud Service Reliability Engineer

Phoenix, AZ

$56.50 - $75.25/hr

... data analytics technologies. Responsibilities of the Cloud Service Reliability Engineer ... GitHub, GitHub Actions, Jenkins, Jira and other CI/CD Tools) * Configuration Management and ...

Paychex

Data Solutions Engineer

Tempe, AZ · On-site +1

$91K - $156K/yr

Develop automation frameworks and CI/CD pipelines using tools like Terraform, GitHub Actions, and ... Work closely with internal teams, including data engineers, data scientists, analytics engineers ...

Paychex

Data Solutions Engineer

Tempe, AZ · On-site

$98K - $160K/yr

Develop automation frameworks and CI/CD pipelines using tools like Terraform, GitHub Actions, and ... Work closely with internal teams, including data engineers, data scientists, analytics engineers ...

Cognite - AI for Industry

Sr. Data Engineer - FP&A

Phoenix, AZ · Remote

$105K - $143K/yr

... GitHub for version control, GitHub Actions for CI/CD, and Terraform for infrastructure and access management. • Willingness to learn and ramp quickly on Cognite Data Fusion (CDF), including Python ...

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All JobsData Analyst Github JobsData Analyst Github Jobs in Arizona

Data Analyst Github information

See Arizona salary details

$31.7K

$77K

$126.7K

How much do data analyst github jobs pay per year?

As of Jul 16, 2026, the average yearly pay for data analyst github in Arizona is $77,011.00, according to ZipRecruiter salary data. Most workers in this role earn between $58,200.00 and $90,400.00 per year, depending on experience, location, and employer.

How does a Data Analyst at GitHub typically collaborate with engineering and product teams?

At GitHub, Data Analysts frequently work alongside engineering and product teams to translate business questions into actionable data insights. They participate in cross-functional meetings, help define key metrics, and build dashboards or reports tailored to the needs of different stakeholders. Effective collaboration requires strong communication skills, as analysts must explain complex data findings to both technical and non-technical colleagues. This collaborative environment fosters continual learning and often provides opportunities to contribute to strategic decisions that impact the direction of products and features.

What are the key skills and qualifications needed to thrive as a Data Analyst on GitHub, and why are they important?

To thrive as a Data Analyst on GitHub, you need strong analytical skills, experience in statistics, and proficiency in data manipulation using languages like Python or SQL, often backed by a relevant degree. Familiarity with data visualization tools (e.g., Tableau, Power BI), Git version control, and GitHub workflows is essential, and certifications in data analysis or related fields are advantageous. Attention to detail, problem-solving, and effective communication are vital soft skills for collaborating on open-source projects and sharing insights. These competencies enable accurate data-driven decision-making, efficient project collaboration, and impactful contributions to the GitHub community.

What are Data Analysts on GitHub?

Data Analysts on GitHub are professionals or contributors who use the platform to share, collaborate, and manage data analysis projects. They leverage GitHub to store datasets, share scripts and code (often in languages like Python or R), and document their analyses using tools like Jupyter Notebooks or Markdown. GitHub enables Data Analysts to version-control their work, collaborate with others through pull requests and issues, and showcase their portfolios to potential employers or collaborators.

What is the difference between Data Analyst Github vs Data Scientist?

AspectData Analyst GithubData Scientist
Required CredentialsBachelor's in Data Analytics, Statistics, or related field; proficiency in SQL, Excel, and visualization toolsBachelor's or Master's in Data Science, Computer Science, or related; knowledge of programming languages like Python or R, machine learning
Work EnvironmentCollaborates with teams to analyze data, create dashboards, and support decision-makingBuilds models, develops algorithms, and performs advanced statistical analysis
Employer & Industry UsageUsed across industries for reporting, data visualization, and business insightsApplied in AI, predictive modeling, and complex data analysis projects

While both roles involve working with data, Data Analyst Github focuses on data visualization, reporting, and supporting business decisions, often using tools like SQL and Excel. Data Scientists perform advanced analytics, build predictive models, and require programming skills in Python or R. The roles overlap in data handling but differ in complexity and technical depth.

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Data Analyst Github jobs near you
Scientific Analyst II

Scientific Analyst II

University of Arizona

Tucson, AZ

Other

Posted 26 days ago

University Of Arizona rating

7.2

Company rating: 7.2 out of 10

Based on 67 frontline employees who took The Breakroom Quiz

345th of 555 rated colleges and universities

Job description

Data Analysis and Machine Learning Pipeline Development:

  • Under moderate guidance collaborate in the design, develop, and execution of machine learning and AI-driven analytical pipelines to analyze large-scale biomedical datasets from UK Biobank, All of Us, Insight, and electronic medical records.
  • Apply supervised and unsupervised machine learning algorithms (e.g., logistic regression, random forests, deep learning) to identify risk factors, biomarkers, and patterns associated with neurodegenerative diseases and the effects of menopausal hormone therapy (MHT) on brain health.
  • Collaborate on the development and validation of predictive models integrating genomic, clinical, lifestyle, and imaging data using general knowledge of principals, theories and concepts.

Drug Repurposing Research and Bioinformatics Analysis:

  • Collaborating in computational drug repurposing analyses to identify existing FDA-approved compounds with potential efficacy for AD, PD, MS, and ALS prevention and treatment. Integrate multi-omics data (genomics, transcriptomics, proteomics) with clinical outcomes data to prioritize drug candidates.
  • Collaborate with wet lab and clinical teams to support translational interpretation of findings.

Epidemiological and Clinical Data Management and Harmonization:

  • Access, curate, harmonize, and manage large population-based datasets including UK Biobank, All of Us, and institutional EMR data.
  • Ensure data quality, reproducibility, and compliance with data use agreements and IRB protocols.
  • Collaborate in the develop and maintenance of reproducible data pipelines using Python, R, and high performance computer.
  • Perform statistical analyses including survival analysis, longitudinal modeling, and causal inference.

Scientific Communication, Dissemination, and Collaboration:

  • Compare and contribute to peer-reviewed manuscripts, conference presentations, and grant applications reporting research findings on MHT, menopause, and neurodegenerative disease.
  • Present results to interdisciplinary research teams, departmental seminars, and external stakeholders.
  • Collaborate closely with Dr. Francesca Vitali, co-investigators, and consortium partners. Maintain thorough documentation of analytical methods to ensure transparency and reproducibility.
  • Participate in lab meetings, journal clubs, and professional development activities.

Research Infrastructure and Continuous Improvement:

  • Maintain and improve lab computational infrastructure, including code repositories (GitHub), analytical workflows, and documentation standards.
  • Evaluate and adopt emerging AI/ML tools and methodologies relevant to brain science research.
  • Assist in training junior lab members or graduate students on data science methods and tools as needed.
  • Stay current with literature in neurodegenerative disease, computational.

Knowledge, Skills and Abilities:

  • Strong theoretical and applied knowledge of machine learning, deep learning, and statistical modeling.
  • Strong data wrangling and preprocessing skills for large, heterogeneous datasets.
  • Expert-level programming skills in Python and/or R; proficiency with ML libraries (scikit-learn, TensorFlow, PyTorch, XGBoost).
  • Knowledge of drug repurposing methodologies or network pharmacology.
  • Knowledge and familiarity with electronic medical records data analysis.
  • Knowledge and proficiency with SQL and database management.
  • Ability to collaborate effectively within interdisciplinary teams spanning data science, neuroscience, clinical research, and epidemiology.
  • Ability to manage multiple concurrent projects and meet deadlines.
  • Ability to critically evaluate scientific literature and translate findings into research hypotheses and analytical strategies.
  • Ability to communicate complex analytical results clearly to both technical and non-technical audiences.

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