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Data Optimization Jobs in Tempe, AZ (NOW HIRING)

As a Data Scientist , you'll be a key contributor in designing, building, and evaluating data ... Design, build, and refine pricing and optimization models, including dynamic pricing, price ...

Data Architect

Chandler, AZ · On-site

$61.50 - $79/hr

Solid understanding of ETL design, orchestration, and optimization in cloud platforms. We are looking for a Data Engineer with strong expertise in AWS, Python, and Conversational Analytics with a ...

As a Data Scientist , you'll be a key contributor in designing, building, and evaluating data ... Design, build, and refine pricing and optimization models, including dynamic pricing, price ...

Data Engineer

Phoenix, AZ · On-site

$113K - $136K/yr

Responsibilities : • Build optimal cloud-based data pipeline in AWS • Build automated data ingestion and ETL processes • Develop and deploy cloud-based web applications Qualifications

Apply statistical modeling, forecasting, classification, regression, clustering, optimization, and other data science techniques to solve business problems. * Support use cases such as demand ...

Sr. Data Engineer

Chandler, AZ · Remote

$117K - $140K/yr

Designs and implements optimized ELT processes to extract, transform, and load data from various sources efficiently. Ensures the reliability, accuracy, and performance of ETL processes and reports ...

Data Engineer

Phoenix, AZ · On-site

$113K - $136K/yr

The Data Engineer is a hands-on technical role focused on designing, developing, and optimizing enterprise data solutions. This individual will play a key role in advancing modern data engineering ...

Senior Data Platform Engineer

Tempe, AZ

$109K - $131K/yr

The role involves designing and optimizing large-scale data pipelines, modernizing cloud-based data ecosystems, and enabling secure, governed data solutions. Strong skills in SQL, Python, PySpark, ET ...

Senior Data Platform Engineer

Tempe, AZ

$109K - $131K/yr

The role involves designing and optimizing large-scale data pipelines, modernizing cloud-based data ecosystems, and enabling secure, governed data solutions. Strong skills in SQL, Python, PySpark, ET ...

Skills & Qualifications * 5-8 years of experience as a SQL/Data Analyst, with strong hands-on expertise in MS SQL (querying, data manipulation, and performance optimization) * Solid understanding of ...

The Data Scientist II balances AI and analytical rigor, speed of execution, and solution ... Experience with common commercial analytics topics (e.g. pricing optimization, customer ...

Data Engineer

Scottsdale, AZ

$114K - $137K/yr

Serves as a technical leader in data engineering, driving best practices in pipeline design, data modeling, and platform optimization. Key Responsibilities: * Design, develop, and maintain end-to-end ...

Data Engineer

Scottsdale, AZ · On-site

$115K - $138K/yr

Proficiency in Hive and SQL optimization. * Understanding of distributed systems and big data architecture. * Knowledge of streaming frameworks (Spark Streaming, Kafka Streams). * Good to have ...

Showing results 21-40

Data Optimization information

What are some typical challenges faced in a data optimization role?

Professionals in Data Optimization often encounter challenges such as working with incomplete or inconsistent datasets, integrating data from multiple sources, and ensuring data quality and accuracy throughout the optimization process. Balancing technical efficiency with business objectives and communicating complex analytical findings in easily understandable ways can also be demanding. Collaboration with cross-functional teams is frequent, requiring both strong technical and interpersonal skills. Overcoming these challenges helps ensure that optimization projects deliver meaningful value and measurable impact for the organization.

What is a data optimization?

A Data Optimization job involves improving the efficiency, accuracy, and accessibility of data within an organization. Professionals in this role analyze large datasets, refine data structures, and implement strategies to enhance data processing and storage. They work with data engineers, analysts, and business teams to ensure data supports performance goals and decision-making. Common tasks include cleaning data, reducing redundancies, and optimizing database queries.

What are the key skills and qualifications needed to thrive in data optimization, and why are they important?

To thrive in Data Optimization, you need strong analytical skills, expertise in data modeling, and a solid foundation in statistics or mathematics, usually supported by a relevant degree. Familiarity with tools such as SQL, Python, R, and data visualization platforms like Tableau, as well as certifications in data analytics or optimization software, is highly beneficial. Effective communication, problem-solving abilities, and a collaborative mindset are key soft skills for this role. These competencies are crucial for translating complex data into actionable insights that drive business efficiency and performance improvements.

What cities near Tempe, AZ are hiring for Data Optimization jobs? Cities near Tempe, AZ with the most Data Optimization job openings:
Infographic showing various Data Optimization job openings in Tempe, AZ as of July 2026, with employment types broken down into 1% As Needed, 81% Full Time, 10% Part Time, and 8% Contract. Highlights an 83% Physical, 3% Hybrid, and 14% Remote job distribution.

Data Scientist II

Master Electronics

Phoenix, AZ • On-site

Full-time

Medical, Life, Retirement, PTO

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