1

Data Science New Grad Jobs in Arizona (NOW HIRING)

Review key metrics and utilize data to make informed decisions We offer flexibility to work from ... You're eager to take on new challenges, learn new skills, and pitch in wherever needed as part of ...

Support data scientists and software engineers in building and deploying new RESTful services. * Apply software engineering best practices including code reviews, version control, testing frameworks ...

Senior Data Engineer, Predictive Modeling

Tempe, AZ · On-site

$101K - $137K/yr

Support data scientists and software engineers in building and deploying new RESTful services. * Apply software engineering best practices including code reviews, version control, testing frameworks ...

Senior Data Engineer, Predictive Modeling

Tempe, AZ · On-site

$101K - $137K/yr

Support data scientists and software engineers in building and deploying new RESTful services. * Apply software engineering best practices including code reviews, version control, testing frameworks ...

As a Decision Science Analyst Lead , you will be at the forefront of creating innovative analytical ... Innovates to create new and emerging data sets, and incorporation (data wrangling, data munging ...

... scientific rigor to the team. This process involves understanding complex business functions, creating new solutions, analyzing structured and unstructured data, forming descriptive analysis and ...

... scientific rigor to the team. This process involves understanding complex business functions, creating new solutions, analyzing structured and unstructured data, forming descriptive analysis and ...

Responsible for reporting forecast data through CRM (Customer Relationship Management) system ... Motivated to learn and apply new technologies * Flexibility/Willingness to travel including ...

Showing results 41-60

Data Science New Grad information

What is a data science new grad?

Data Science New Grad roles are entry-level positions designed for recent graduates who have completed a degree in data science, computer science, statistics, or a related field. These roles typically involve working with data to analyze trends, build predictive models, and support business decision-making. New grads are expected to have foundational knowledge in programming, statistics, and machine learning, but are not required to have extensive work experience. These roles often offer mentorship and training to help new professionals grow their technical and analytical skills. Companies hire Data Science New Grads to bring fresh perspectives and to develop future data science talent.

What are the key skills and qualifications needed to thrive as a data science new grad?

To thrive as a Data Science New Grad, you need a strong foundation in statistics, programming (typically Python or R), and data analysis, often supported by a degree in computer science, mathematics, or a related field. Familiarity with machine learning frameworks (such as TensorFlow or scikit-learn), data visualization tools, and SQL databases is highly valued. Strong problem-solving abilities, communication skills, and curiosity help new grads stand out when interpreting data and presenting insights. These competencies are crucial for transforming complex data into actionable business solutions and collaborating effectively within multidisciplinary teams.

What types of projects can a data science new grad expect to work on during their first year?

As a Data Science New Grad, you can expect to work on a variety of projects such as cleaning and preprocessing data, developing predictive models, and assisting with data visualization and reporting. You may also collaborate closely with product managers, engineers, and senior data scientists to translate business problems into analytical solutions. Early projects often focus on building foundational skills and understanding the company’s data infrastructure, while gradually increasing in complexity as you gain experience. This hands-on exposure is designed to help you grow technically and understand how data science supports organizational goals.

What cities in Arizona are hiring for Data Science New Grad jobs?

Cities in Arizona with the most Data Science New Grad job openings:

Infographic showing various Data Science New Grad 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 85% Physical, 4% Hybrid, and 11% Remote job distribution.

Basketball Data Scientist, Phoenix Suns

Player 15 Group

Phoenix, AZ • On-site

Full-time

Posted 28 days ago


Job description

At Player 15 Group, we aren't just building a team: we're crafting a legacy.
We're a collective of visionaries who consistently put people first, knowing that true greatness is forged through shared passion and purpose. Service focused to our core, we're driven by an insatiable desire to innovate and elevate every experience. Our strength lies in unity, where diverse talents converge to achieve extraordinary feats, and we infuse every endeavor with genuine joy. Here, a relentless pursuit of growth isn't just encouraged-it's the very air we breathe. If you're ready to transcend expectations, unlock unparalleled potential, and dedicate your energy to something truly special, your moment to make an indelible mark on the future of sports and live entertainment starts now.
The Basketball Analytics team partners across Basketball Operations to transform data, research, and technology into actionable insights for front office, coaching, scouting, player development, and basketball strategy stakeholders.
As a Basketball Data Scientist, your practical day-to-day and forward-thinking work will focus on turning complex basketball questions into rigorous analysis, clear models, useful tools, and decision-ready recommendations. Working closely with Basketball Analytics, Engineering, and Basketball Operations, you will own high-impact research and projects that connect technical rigor with real basketball insights.
What You Will Do
  • Own high-impact basketball data science and analysis initiatives.
    • Translate ambiguous basketball questions into clear analytical plans, research designs, models, tools, and recommendations
    • Conduct basketball research using statistical modeling, machine learning, exploratory analysis, and domain expertise to uncover actionable insights
    • Build, validate, and maintain models that help evaluate players, teams, lineups, tactics, and basketball decision-making questions
    • Work with large and complex basketball datasets, including tracking/spatiotemporal data, play-by-play, event data, lineup/personnel data, scouting information, and other internal sources

  • Develop tools, workflows, and data products that turn research into decisions.
  • Write clean, reproducible code in Python or R for analysis, modeling, reporting, and internal workflows
  • Build internal tools, dashboards, visualizations, and workflows when needed to move projects forward quickly
  • Partner with the Engineering team to productionalize high-value model outputs, tools, and data products
  • Document methods, assumptions, limitations, and outputs clearly so work can be reused, reviewed, and extended by the broader analytics team

  • Support basketball stakeholders with clear analysis and communication
  • Collaborate with front office, coaching, scouting, player development, and basketball strategy groups to ensure analysis is connected to real basketball decisions
  • Communicate complex technical findings through clear recommendations, written reports, visualizations, and presentations
  • Help scope problems, prioritize work, and determine when analysis is rigorous enough to inform decisions
  • Use basketball judgment to interpret model outputs, identify limitations, and translate findings into practical next steps

  • Drive innovation and special projects within Basketball Analytics
    • Stay current with relevant research, modeling approaches, and basketball analytics methods
    • Identify opportunities to bring new ideas, methods, and data sources into the organization
    • Use unique basketball data and internal context to create models and insights that are difficult to replicate externally
    • Other duties as assigned

Growth Areas
  • Basketball decision-support models
  • Develop and refine models that help the organization evaluate players, teams, lineups, tactics, and strategic basketball questions
  • Create tools that make model outputs easier to interpret, compare, and apply in basketball contexts
  • Improve the way uncertainty, sample size, role, context, and fit are incorporated into analysis

  • Applied research and model validation
  • Strengthen research standards for testing, validation, backtesting, documentation, and reproducibility
  • Explore new modeling approaches and determine when they can improve existing workflows
  • Translate research into practical outputs that can be used by basketball stakeholders

  • Internal tools and operational workflows
    • Build and improve tools, reports, and dashboards that help stakeholders answer recurring basketball questions
    • Partner with Engineering to move high-value prototypes into more durable, scalable products
    • Create reusable workflows that improve the speed, consistency, and quality of analytics work

People and Services
  • Integrated working with Basketball Analytics leadership and team members
  • Partnership with Engineering on data products, internal tools, and model deployment workflows
  • Support for front office, coaching, scouting, player development, and basketball strategy stakeholders through timely, decision-oriented analysis.
  • Cross-functional collaboration to ensure technical work is grounded in basketball context and connected to organizational priorities

What You'll Bring
  • Basketball Curiosity and Judgment - A strong desire to understand the game, ask better questions, and connect analysis to basketball decision-making
  • Technical Rigor - Strong statistical, machine learning, and research fundamentals with the ability to validate work and communicate uncertainty.
  • Practical Builder - Ability to move from idea to prototype quickly, while writing clean and reproducible Python or R code
  • Clear Communicator - Ability to translate complex technical work into clear, concise recommendations for technical and non-technical stakeholders.
  • Ownership Mindset - Comfortable taking responsibility for ambiguous problems and driving work from question to insight
  • Collaborative Teammate - Ability to work effectively across Analytics, Engineering, and basketball departments with a service-oriented approach.
  • Data Science Foundation - Professional experience in data science, applied science, research science, or a similar analytical field; expertise in Python or R for data science and proficient SQL skills
  • Basketball Analytics Experience - Prior sports analytics experience with a college, professional, or NBA team is a plus

The Player 15 Group is committed to employing a diverse workforce. Qualified applicants will receive consideration without regard to race, color, religion, sex, national origin, age, sexual orientation, gender identity, gender expression, veteran status, or disability.
Please note this job description is not designed to cover every activity, duty, or responsibility. Duties, responsibilities, and activities may change at any time with or without notice.
For questions about this career opportunity, please contact our People & Culture Recruiting team at recruiting@suns.com