Associate Computer Science Jobs in Glendale, AZ (NOW HIRING)

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.

• 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

• 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

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 

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 succeed. Master 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. 

• 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