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Associate Scientist Jobs in Arizona (NOW HIRING)

As a Data Scientist , you'll be a key contributor in designing, building, and evaluating data ... Databricks certifications (e.g., Machine Learning Associate/Professional) * Knowledge of model ...

In the role of Data Scientist I, we'll count on you to: Handle highly sensitive and confidential ... Associate or Bachelor's degree Required Qualifications * A degree in a closely related field or ...

Data Scientist

Chandler, AZ · On-site

$90 - $120/hr

Data Scientist / Senior Data Scientist We are seeking a highly skilled Data Scientist with strong experience in Generative AI, traditional Machine Learning, and ML Ops. The ideal candidate will have ...

Data Scientist / Senior Data Scientist We are seeking a highly skilled Data Scientist with strong experience in Generative AI, traditional Machine Learning, and ML Ops. The ideal candidate will have ...

Data Scientist / Senior Data Scientist We are seeking a highly skilled Data Scientist with strong experience in Generative AI, traditional Machine Learning, and ML Ops. The ideal candidate will have ...

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Associate Scientist information

See Arizona salary details

$17

$33

$53

How much do associate scientist jobs pay per hour?

As of Sep 6, 2026, the average hourly pay for associate scientist in Arizona is $33.48, according to ZipRecruiter salary data. Most workers in this role earn between $25.96 and $38.08 per hour, depending on experience, location, and employer.

What does an associate scientist do?

An Associate Scientist is a professional who supports research and development projects, typically in fields like biotechnology, pharmaceuticals, or environmental science. They conduct experiments, analyze data, and document results under the supervision of senior scientists. Associate Scientists play a key role in advancing scientific knowledge and product development by performing laboratory tasks, maintaining equipment, and following established protocols. Their work contributes to discoveries, quality control, and regulatory compliance within their organization.

What is an associate scientist?

An associate scientist takes on more responsibilities than an assistant scientist, supporting research and each experiment under the lead scientist, often in a laboratory environment. As an associate scientist, there are many industries you can work in, including the research field where the lead scientist oversees your project, and you help author papers. Many pharmaceutical companies hire associate scientists to analyze samples to develop drugs and assist with preclinical and clinical studies. Private companies need you to produce specialty chemicals for their clients. Materials scientists at the associate level conduct research and test the properties of metals, plastics, and other materials for their use in new products and packaging. Some positions have duties that include training other team members and overseeing students and fellows.

What are the key skills and qualifications needed to thrive as an associate scientist, and why are they important?

To thrive as an Associate Scientist, you generally need a bachelor’s or master’s degree in a relevant scientific field, along with strong analytical and laboratory skills. Familiarity with laboratory information management systems (LIMS), data analysis software, and standard operating procedures (SOPs) is often required. Attention to detail, problem-solving abilities, and effective teamwork are vital soft skills that distinguish top performers. These skills ensure accurate data collection, reliable experimental outcomes, and productive collaboration within research or product development teams.

What are some common challenges an associate scientist might face when transitioning from academia to industry?

Associate Scientists moving from academia to industry often encounter challenges such as adapting to a faster-paced environment and focusing on project-driven outcomes rather than open-ended research. In industry, there is a stronger emphasis on teamwork, meeting strict deadlines, and following standardized protocols. Adjusting to these expectations, learning new technologies, and effectively communicating results to cross-functional teams are key areas where new hires may need support.

What is the difference between Associate Scientist vs Research Scientist?

AspectAssociate ScientistResearch Scientist
Required CredentialsBachelor's or Master's degree in a relevant field; some roles may require a PhDTypically a Master's or PhD in a related discipline
Work EnvironmentLaboratories, research facilities, industry settingsResearch labs, academic institutions, industry
Employer & Industry UsageBiotech, pharmaceuticals, academia, governmentBiotech, pharmaceuticals, academia, government
Common Search & Comparison IntentUnderstanding entry-level or mid-level research rolesAdvanced research roles, career progression

Associate Scientists and Research Scientists often work in similar environments within biotech, pharma, or academic sectors. The main difference lies in experience and educational requirements, with Research Scientists typically holding higher degrees and engaging in more independent or advanced research. Both roles are essential for scientific progress, but Research Scientists usually have more responsibility and autonomy in their projects.

Is an associate scientist entry level?

An associate scientist position is often considered an entry-level or early-career role in research and development, typically requiring a bachelor's or master's degree in a relevant field. It involves performing experiments, data analysis, and supporting scientific projects, with opportunities for skill development and advancement. However, some organizations may require prior experience or specific certifications depending on the complexity of the work.

What degree do you need to be an associate scientist?

An associate scientist typically needs at least a bachelor's degree in a relevant field such as biology, chemistry, or related sciences. Advanced roles may require a master's degree or higher, along with laboratory skills and experience with scientific tools and techniques.

What are the most commonly searched types of Scientist jobs in Arizona?

The most popular types of Scientist jobs in Arizona are:

What job categories do people searching Associate Scientist jobs in Arizona look for?

The top searched job categories for Associate Scientist jobs in Arizona are:

What cities in Arizona are hiring for Associate Scientist jobs?

Cities in Arizona with the most Associate Scientist job openings:

What are popular job titles related to Associate Scientist jobs in AZ?

For Associate Scientist jobs in AZ, the most frequently searched job titles are:

Infographic showing various Associate Scientist job openings in Arizona as of August 2026, with employment types broken down into 1% As Needed, 71% Full Time, 25% Part Time, 2% Temporary, and 1% Contract. Highlights an 96% Physical, 1% Hybrid, and 3% Remote job distribution, with an average salary of $69,634 per year, or $33.5 per hour.

Data Scientist II

Master Electronics

Phoenix, AZ • On-site

Full-time

Medical, Life, Retirement, PTO

Re-posted 29 days ago


Job description

To be a family that uses our collective superpowers to do significant good.

Master Electronics has an exciting career opportunity for a Data Scientist.


As a Data Scientist, you'll be a key contributor in designing, building, and evaluating data-driven decision systems, with a strong emphasis on pricing optimization, experimentation (A/B testing), and causal analysis that directly influence product and business outcomes.



What you will do?
  • Design, build, and refine pricing and optimization models, including dynamic pricing, price elasticity estimation, margin optimization, and demand forecasting, that directly drive revenue and profitability decisions
  • Own the experimentation lifecycle: design and run A/B and multivariate tests, define success metrics and guardrails, determine sample sizes and test duration, analyze results with statistical rigor, and communicate causal impact to stakeholders
  • Apply causal inference techniques (uplift modeling, difference-in-differences, synthetic controls, instrumental variables) where randomized experiments aren't feasible
  • Translate business problems into ML solutions; build models for prediction, classification, or recommendation; implement feature engineering, model training, hyperparameter tuning, evaluation, and deployment
  • Develop scalable data pipelines on Databricks; integrate experimentation and ML systems with modern data and MLOps platforms (Databricks, MLflow); establish CI/CD pipelines, version control, testing, and monitoring to ensure model quality and reliability
  • Partner with software engineers, data engineers, product managers, and subject-matter experts; present insights and recommendations to technical and non-technical stakeholders; translate complex analyses into clear narratives
  • Research and apply emerging ML techniques; contribute to improving team standards and mentoring junior team members


What you bring to the table!
  • 3-5 years of professional experience as a data scientist or ML engineer, with a proven record of building and deploying ML models in production
  • Hands-on experience with pricing, revenue, or marketing optimization, such as price elasticity modeling, dynamic pricing, promotion optimization, or mathematical optimization methods
  • Demonstrated expertise in A/B testing and experimentation: hypothesis design, power analysis, sequential testing, guardrail metrics, and interpreting results under real-world constraints (novelty effects, interference, heterogeneous treatment effects)
    Hands-on Databricks experience for building and deploying data science workloads at scale
  • Master's degree in Computer Science, Statistics, Mathematics, Engineering, Operations Research, or a related quantitative fi eld, or a Bachelor's degree with 5+ years of equivalent professional experience
  • Strong programming skills in Python (plus experience in JavaScript), with proficiency in ML libraries (scikit-learn, PyTorch), data manipulation (pandas, SQL), and statistical analysis
  • Solid grounding in statistics: hypothesis testing, confidence intervals, regression, and Bayesian methods
  • Knowledge of MLOps tools and cloud platforms, especially Databricks (Spark, MLfl ow), AWS (S3,Redshift, SageMaker), or similar services
  • Excellent communication skills; ability to explain complex technical concepts to both technical and business audiences and to collaborate effectively across teams
  • Demonstrated ability to work independently on complex problems, manage multiple projects simultaneously, and deliver results in a fast-paced environment
    Preferred Qualifications
  • Advanced degree (Master's or PhD) in a relevant field (Statistics, Machine Learning, AI, Operations Research, Economics/Econometrics, etc.)
  • Experience with B2B or ecommerce pricing, such as quote optimization, contract pricing, or price-list management in a distribution or catalog business
  • Familiarity with experimentation platforms (in-house or commercial, e.g., Optimizely, Statsig, GrowthBook)and metric frameworks
  • Exposure to industry-specific domains such as ecommerce, marketing analytics, risk/fraud, supply chain, or logistics
  • Fluency with big data frameworks (Spark, Hadoop), streaming systems, and container/orchestration tools(Docker, Kubernetes)
  • Databricks certifications (e.g., Machine Learning Associate/Professional)
  • Knowledge of model explainability, interpretability techniques, and responsible AI

Why do you want to work with us

Stay Healthy: World-class and affordable insurance plans ensure you and your family stay healthy 

Secure Your Future: 401(k) match program where you are vested from day-one  

Invest in Your Education: Tuition assistance empowers you to further your education and career 

Employee Assistance Program (EAP) and other incentives: Access to Perspectives, Healthcare Advocate, Working Advantage Discount Program, and more 

Enjoy Work-Life-Harmony: Paid holidays, PTO accrual, Floating Holiday, and supportive personal and parental leave policies 

Do Significant Good: Company-sponsored donation match 3 for 1, Volunteer Time Off (VTO) to give back to the community, and Employee Resource Groups 

Provide Additional Financial Security: Company-funded and voluntary AD&D Life Insurance for you and your loved ones 

If you want to learn more about our comprehensive benefits, visit: https://careers.masterelectronics.com/benefits-wellness 



Equal Opportunity Employer

At Master Electronics, we thrive in a fast-paced, entrepreneurial environment where flexibility, professionalism, and a self-starter mindset aren’t just preferred—they’re essential. Headquartered in sunny Phoenix, AZ, we’re a leading global authorized distributor of electronic components, and have been proudly family-owned for over 50 years. 

What’s our secret? It’s simple: strong relationships, responsive service, and genuine added value. These principles have fueled our growth, allowing us to serve hundreds of thousands of customers in close partnership with world-class suppliers across the globe. 

We’re also deeply committed to building a workplace where everyone feels respected, supported, and empowered to succeedMaster Electronics is committed to providing equal employment opportunities for all applicants and employees. We do not unlawfully discriminate based on race, color, religion, sex (including pregnancy, gender identity, and sexual orientation), national origin, age, disability, veteran status, marital status, creed, or any other protected characteristic. 

We provide reasonable accommodations in compliance with the ADA and other applicable laws, and we strictly prohibit harassment of any kind. 

This commitment applies to every part of our workplace—from recruitment and hiring to promotions, training, compensation, benefits, and even company events. 

Qualifications:
  • 3-5 years of professional experience as a data scientist or ML engineer, with a proven record of building and deploying ML models in production
  • Hands-on experience with pricing, revenue, or marketing optimization, such as price elasticity modeling, dynamic pricing, promotion optimization, or mathematical optimization methods
  • Demonstrated expertise in A/B testing and experimentation: hypothesis design, power analysis, sequential testing, guardrail metrics, and interpreting results under real-world constraints (novelty effects, interference, heterogeneous treatment effects)
    Hands-on Databricks experience for building and deploying data science workloads at scale
  • Master's degree in Computer Science, Statistics, Mathematics, Engineering, Operations Research, or a related quantitative fi eld, or a Bachelor's degree with 5+ years of equivalent professional experience
  • Strong programming skills in Python (plus experience in JavaScript), with proficiency in ML libraries (scikit-learn, PyTorch), data manipulation (pandas, SQL), and statistical analysis
  • Solid grounding in statistics: hypothesis testing, confidence intervals, regression, and Bayesian methods
  • Knowledge of MLOps tools and cloud platforms, especially Databricks (Spark, MLfl ow), AWS (S3,Redshift, SageMaker), or similar services
  • Excellent communication skills; ability to explain complex technical concepts to both technical and business audiences and to collaborate effectively across teams
  • Demonstrated ability to work independently on complex problems, manage multiple projects simultaneously, and deliver results in a fast-paced environment
    Preferred Qualifications
  • Advanced degree (Master's or PhD) in a relevant field (Statistics, Machine Learning, AI, Operations Research, Economics/Econometrics, etc.)
  • Experience with B2B or ecommerce pricing, such as quote optimization, contract pricing, or price-list management in a distribution or catalog business
  • Familiarity with experimentation platforms (in-house or commercial, e.g., Optimizely, Statsig, GrowthBook)and metric frameworks
  • Exposure to industry-specific domains such as ecommerce, marketing analytics, risk/fraud, supply chain, or logistics
  • Fluency with big data frameworks (Spark, Hadoop), streaming systems, and container/orchestration tools(Docker, Kubernetes)
  • Databricks certifications (e.g., Machine Learning Associate/Professional)
  • Knowledge of model explainability, interpretability techniques, and responsible AI
Education:UNAVAILABLEEmployment Type: FULL_TIME