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Phd Causal Inference Jobs in Phoenix, AZ (NOW HIRING)

Data Scientist II

Phoenix, AZ · On-site

$120 - $160/hr

  • Medical

  • Life

  • Retirement

  • PTO

Apply causal inference techniques (uplift modeling, difference-in-differences, synthetic controls ... Advanced degree (Master's or PhD) in a relevant field (Statistics, Machine Learning, AI, Operations ...

Data Scientist II

Phoenix, AZ · On-site

  • Medical

  • Life

  • Retirement

  • PTO

Apply causal inference techniques (uplift modeling, difference-in-differences, synthetic controls ... Advanced degree (Master's or PhD) in a relevant field (Statistics, Machine Learning, AI, Operations ...

Data Scientist II

Phoenix, AZ · On-site

$120 - $170/hr

  • Medical

  • Life

  • Retirement

  • PTO

Apply causal inference techniques (uplift modeling, difference-in-differences, synthetic controls ... Advanced degree (Master's or PhD) in a relevant field (Statistics, Machine Learning, AI, Operations ...

Data Scientist II

Phoenix, AZ · On-site

  • Medical

  • Life

  • Retirement

  • PTO

Apply causal inference techniques (uplift modeling, difference-in-differences, synthetic controls ... Advanced degree (Master's or PhD) in a relevant field (Statistics, Machine Learning, AI, Operations ...

Data Scientist II

Phoenix, AZ

  • Medical

  • Life

  • Retirement

  • PTO

Apply causal inference techniques (uplift modeling, difference-in-differences, synthetic controls ... Advanced degree (Master's or PhD) in a relevant field (Statistics, Machine Learning, AI, Operations ...

Phd Causal Inference information

See Phoenix, AZ salary details

$39.7K

$122.1K

$177.2K

How much do phd causal inference jobs pay per year?

As of Aug 14, 2026, the average yearly pay for phd causal inference in Phoenix, AZ is $122,057.00, according to ZipRecruiter salary data. Most workers in this role earn between $104,300.00 and $137,000.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a PhD causal inference researcher?

To thrive as a PhD Causal Inference researcher, you need advanced knowledge of statistics, econometrics, and causal modeling, typically supported by a doctoral degree in a quantitative field. Familiarity with statistical programming languages (such as R or Python), specialized software (like STATA or SAS), and experience with experimental or quasi-experimental methods are essential. Strong analytical thinking, attention to detail, and the ability to communicate complex findings clearly make a candidate stand out. These skills ensure rigorous, credible research that can inform policy, product development, or scientific understanding by accurately identifying causal relationships.

What collaborative opportunities can a PhD specializing in causal inference expect within a multidisciplinary research team?

PhD professionals in Causal Inference frequently collaborate with experts from fields such as epidemiology, economics, computer science, and public health. They often work closely with data scientists, subject matter experts, and statisticians to design studies, interpret complex datasets, and develop robust analytical models. This multidisciplinary environment fosters continuous learning and often leads to co-authorship on research publications, participation in grant writing, and involvement in high-impact policy or product decisions. Effective communication and teamwork skills are essential to translate technical findings for diverse audiences and drive actionable insights.

What is a PhD in causal inference?

A PhD in Causal Inference is an advanced research degree focused on understanding and identifying cause-and-effect relationships using statistical and computational methods. Students in this field learn to design studies, analyze data, and develop new methodologies to answer complex causal questions in areas such as social sciences, medicine, economics, and artificial intelligence. Graduates often work in academia, research institutions, or industries where evidence-based decision-making is essential.

What are popular job titles related to Phd Causal Inference jobs in Phoenix, AZ?

For Phd Causal Inference jobs in Phoenix, AZ, the most frequently searched job titles are:

Data Scientist II

Master-Electronics

Phoenix, AZ • On-site

$120 - $160/hr

Other

Medical, Life, Retirement, PTO

Re-posted 6 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 field, 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, MLflow), 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 e‑commerce 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 e‑commerce, 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.

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.

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