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Decision Science Jobs in Arizona (NOW HIRING)

State Farm

Data Scientist

Tempe, AZ · Hybrid

Our data science teams also embrace staying current with the evolving data science landscape ... Collaborate with other team members on scoping solutions and project decision points * Present on ...

Intel

Senior AI / Data Science Engineer

Phoenix, AZ · On-site

$105K - $143K/yr

... driven decision making and measurable business impact. * Develop and deploy Large Language Model ... Data Science, Machine Learning, Artificial Intelligence, Advanced Analytics. Performing yield ...

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Decision Science information

See Arizona salary details

$10.3K

$70.5K

$91.8K

How much do decision science jobs pay per year?

As of Aug 23, 2026, the average yearly pay for decision science in Arizona is $70,473.00, according to ZipRecruiter salary data. Most workers in this role earn between $58,200.00 and $87,100.00 per year, depending on experience, location, and employer.

What is a decision science?

A Decision Science job involves using data, analytics, and mathematical models to guide business decisions. Professionals in this field apply statistical analysis, machine learning, and optimization techniques to solve complex problems. They work closely with stakeholders to translate data insights into strategic actions. Decision Science roles are common in industries like finance, healthcare, marketing, and technology. The goal is to enhance decision-making processes by leveraging data-driven approaches.

What does a decision science do?

In a Decision Science role, your day often involves analyzing large datasets, building predictive models, and interpreting results to help inform business strategies or solve operational problems. You may collaborate closely with cross-functional teams such as product, marketing, and engineering to translate insights into actionable recommendations. Other daily activities typically include exploratory data analysis, preparing reports or visualizations, and presenting findings to both technical and non-technical stakeholders. This role offers fast-paced, intellectually rewarding work with ample opportunity for professional growth in both technical and strategic career paths.

What are the key skills and qualifications needed to thrive in decision science?

To excel in Decision Science, you need a strong background in statistics, mathematics, data analysis, and business acumen, often supported by a degree in data science, economics, or a related field. Expertise with tools like Python, R, SQL, data visualization platforms, and familiarity with machine learning models or certifications is highly valuable. Strong problem-solving, critical thinking, and communication skills distinguish top performers in this role. Combining these abilities allows professionals to turn complex data into strategic insights that drive effective business decisions.

How much does a decision scientist make?

Decision scientists typically earn a median salary ranging from $80,000 to $130,000 annually, depending on experience, education, and location. Senior roles or those with advanced skills in data analysis, machine learning, and programming can earn higher salaries, often exceeding $150,000. Compensation also varies based on industry and company size.

Is decision science a good career?

Decision science is a growing field that involves analyzing data to inform strategic choices, often requiring skills in statistics, data analysis, and programming. It offers opportunities in various industries such as finance, healthcare, and technology, with roles typically requiring a strong analytical background and proficiency in tools like Python or R. The career can be rewarding for those interested in data-driven decision-making and problem-solving.

What is a decision science job?

A decision science job involves analyzing data and applying quantitative methods to help organizations make informed decisions. Professionals in this field often use statistical tools, machine learning, and data visualization to solve complex problems and improve strategic outcomes.

What kind of jobs use decision science?

Decision science is used in roles such as data analysts, data scientists, operations researchers, and business analysts, where analyzing data and modeling decision-making processes are essential. These jobs often require skills in statistics, data visualization, and tools like Python, R, or SQL to inform strategic choices across industries like finance, healthcare, marketing, and technology.

What are popular job titles related to Decision Science jobs in Arizona?

For Decision Science jobs in Arizona, the most frequently searched job titles are:

What job categories do people searching Decision Science jobs in Arizona look for?

The top searched job categories for Decision Science jobs in Arizona are:

Decision Science jobs near you
Infographic showing various Decision Science job openings in Arizona as of August 2026, with employment types broken down into 1% As Needed, 85% Full Time, 10% Part Time, 2% Temporary, and 2% Contract. Highlights an 89% Physical, 3% Hybrid, and 8% Remote job distribution, with an average salary of $70,473 per year, or $33.9 per hour.

Vice President - Data Science

Caris Life Sciences

Tempe, AZ • On-site

Full-time

Re-posted 6 days ago

Job description

At Caris, we understand that cancer is an ugly word-a word no one wants to hear, but one that connects us all. That's why we're not just transforming cancer care-we're changing lives.
We introduced precision medicine to the world and built an industry around the idea that every patient deserves answers as unique as their DNA. Backed by cutting-edge molecular science and AI, we ask ourselves every day: "What would I do if this patient were my mom?" That question drives everything we do.
But our mission doesn't stop with cancer. We're pushing the frontiers of medicine and leading a revolution in healthcare-driven by innovation, compassion, and purpose.
Join us in our mission to improve the human condition across multiple diseases. If you're passionate about meaningful work and want to be part of something bigger than yourself, Caris is where your impact begins.
Position Summary
The Vice President, Data Science provides senior leadership for Caris' AI-driven clinical insights and predictive modeling initiatives. This role leads the development of novel AI signatures leveraging Caris' large-scale clinico-genomic database to identify molecular characteristics of disease that are prognostic of patient outcomes or predictive of response to therapy.
The Vice President oversees a multidisciplinary team of data scientists, computational biologists, and translational researchers responsible for identifying clinically meaningful questions, developing and validating AI-based molecular signatures, and translating discoveries into scalable clinical reporting capabilities. Partnering with Executive Leadership, R&D, Clinical Development, Medical Affairs, Bioinformatics, Regulatory Affairs, and Commercial teams, this role ensures delivery of scientifically rigorous, clinically meaningful, and operationally scalable AI innovations that advance precision medicine.
Job Responsibilities
  • Define and execute the strategy for AI-driven clinical insight and molecular signature development across Caris' molecular profiling platforms.
  • Identify clinically relevant questions where advanced analytics can deliver prognostic or predictive insights.
  • Oversee development of AI signatures integrating genomic, transcriptomic, proteomic, and clinical outcomes data.
  • Establish governance and standards for model development, validation, documentation, and lifecycle management.
  • Collaborate with Regulatory and Clinical Development teams to ensure appropriate validation and evidence generation.
  • Lead implementation of AI products within a regulated CAP/CLIA clinical environment.
  • Oversee engineering and production deployment of AI pipelines within Caris' clinical reporting infrastructure.
  • Ensure scalable, reproducible, auditable computational pipelines and canonical data models.
  • Lead development of clinically interpretable reporting frameworks for physicians.
  • Partner with Product and Commercial teams to integrate AI insights into clinical reports and decision-support tools.
  • Build, mentor, and lead high-performing teams of data scientists and computational biologists.
  • Set organizational goals, budgets, roadmaps, OKRs, and performance metrics aligned with corporate priorities.
  • Champion a culture of scientific rigor, accountability, transparency, and continuous improvement.

Required Qualifications
  • PhD in Data Science, Biostatistics, Computer Science, Biomedical Engineering, or a related field.
  • 10+ years of experience building and implementing supervised and unsupervised machine learning models for complex problem solving.
  • Expert proficiency in Python (pandas, NumPy, statistical and ML libraries) and SQL.
  • Strong expertise in machine learning, statistical modeling, and large-scale biomedical data analysis.
  • Experience working with multi-omic datasets including genomics, transcriptomics, and proteomics.
  • Experience leveraging large clinical datasets for biomarker discovery, predictive modeling, or outcomes research.
  • Working knowledge of regulatory considerations for algorithm development in clinical diagnostics environments.
  • Demonstrated people leadership and direct management experience with accountability for large-scale outcomes.
  • Outstanding verbal and written communication skills.
  • Proficient in Microsoft Office Suite including Word, Excel, Outlook, and PowerPoint.
  • This is an onsite role based at our Phoenix, AZ office and requires regular in-person presence.

Preferred Qualifications
  • Experience working in regulated clinical laboratory environments (CAP/CLIA).
  • Familiarity with cloud computing platforms and large-scale data infrastructures.
  • Experience translating advanced analytics into physician-facing clinical products.

Physical Demands
  • Ability to sit, stand, and work at a computer for extended periods of time.

Training
  • All job-specific, safety, and compliance training assigned based on job responsibilities.

Other
  • May require occasional after-hours work to meet deadlines.
  • May require occasional travel.

Conditions of Employment: Individual must successfully complete pre-employment process, which includes criminal background check, drug screening, credit check ( applicable for certain positions) and reference verification.
This job description reflects management's assignment of essential functions. Nothing in this job description restricts management's right to assign or reassign duties and responsibilities to this job at any time.
Caris Life Sciences is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, religion, color, national origin, gender, gender identity, sexual orientation, age, status as a protected veteran, among other things, or status as a qualified individual with disability.

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