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Data Science Phd Jobs in Nevada (NOW HIRING)

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Data Science Phd information

What is a data science PhD?

A Data Science PhD is a doctoral-level degree focused on advanced research in data science, which combines elements of statistics, computer science, and domain expertise. Students in a Data Science PhD program typically work on developing new methods for analyzing large datasets, creating machine learning algorithms, and addressing complex problems in areas such as artificial intelligence, data mining, and predictive analytics. Graduates are prepared for careers in academia, research, and industry, where they can lead data-driven projects and contribute to advancements in the field.

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

To thrive as a Data Science PhD, you need advanced expertise in statistics, machine learning, data analysis, and a doctoral degree in a quantitative field. Proficiency in programming languages like Python or R, experience with big data frameworks (e.g., Spark, Hadoop), and familiarity with data visualization tools are typically required. Critical thinking, problem-solving, and strong communication skills help you translate complex data insights for diverse stakeholders. These skills are vital for driving innovative research, making data-driven decisions, and contributing impactful solutions in data-centric environments.

What are some common challenges faced by data science PhDs when transitioning from academia to industry roles?

Data Science PhDs often encounter challenges such as adapting to the faster pace and collaborative nature of industry projects compared to academic research. In industry, there is a greater emphasis on delivering practical solutions within tight deadlines and working closely with cross-functional teams like engineering and product management. Additionally, data science work in industry may require balancing technical rigor with business impact, often prioritizing actionable insights over exhaustive analysis. Building strong communication and stakeholder management skills can help ease this transition.

What can I do with a data science PhD?

A data science PhD prepares individuals for advanced roles in research, analytics, and machine learning across industries such as technology, finance, healthcare, and academia. Graduates can work as data scientists, machine learning engineers, research scientists, or data analysts, often utilizing programming languages like Python or R and tools such as TensorFlow or SQL. The degree also enables roles involving complex data modeling, statistical analysis, and developing innovative data-driven solutions.

What are popular job titles related to Data Science Phd jobs in Nevada?

For Data Science Phd jobs in Nevada, the most frequently searched job titles are:

Infographic showing various Data Science Phd job openings in Nevada as of August 2026, with employment types broken down into 1% As Needed, 88% Full Time, 9% Part Time, and 2% Contract. Highlights an 84% Physical, 4% Hybrid, and 12% Remote job distribution.

Vice President, Data Science

Las Vegas, NV • On-site

Aristocrat Technologies, Inc.
Amusement, Gambling, and Recreation • 11 - 50 employees

Full-time

Medical, Retirement, PTO

Posted 26 days ago


Key responsibilities

  • Define and implement the enterprise Data Science strategy, roadmap, and operating model.

  • Partner with senior business and technology leaders to identify, prioritize, and scale Data Science, machine learning, and AI opportunities.

  • Lead, develop, and grow a high-performing Data Science organization through multiple levels of leadership.


Aristocrat Technologies rating

6.3

Company rating: 6.3 out of 10

Based on 9 frontline employees who took The Breakroom Quiz


Job description

At Aristocrat, we are passionate about bringing happiness to life through the power of play. As a world leader in gaming content and technology, we strive to build outstanding experiences for our customers and players. The Vice President, Data Science defines and delivers Aristocrat's enterprise Data Science strategy and builds a Data Science organization that delivers business impact through machine learning, statistical modeling, advanced analytics, and AI. As a member of the Enterprise Data & Analytics leadership team, this role partners with senior business and technology leaders to shape strategy, accelerate innovation, and enable data-driven decision making across the enterprise.
What You'll Do
  • Define and implement the enterprise Data Science strategy, roadmap, and operating model.
  • Serve as the executive advisor on Data Science strategy, investments, risks, and emerging opportunities.
  • Partner with executive leaders to identify, prioritize, and scale Data Science, machine learning, and AI opportunities that solve business problems, improve decision making, and create measurable business value and competitive advantage.
  • Evaluate emerging Data Science, AI, and machine learning technologies, tools, and techniques, and establish a roadmap for adoption where they provide relevant business value.
  • Lead, develop and grow a high-performing organization through multiple levels of leadership, including Directors, Managers, Data Scientists, and Machine Learning Engineers.
  • Establish enterprise standards, governance, and operating principles for machine learning, statistical modeling, experimentation, optimization, decision science, and responsible AI.
  • Define the enterprise strategy and architecture for model lifecycle management, including model development, deployment, monitoring, governance, and continuous improvement.
  • Collaborate with Architecture, Data Governance, Platform Engineering, and Analytics teams to ensure scalable and balanced delivery of Data Science capabilities.
  • Drive enterprise adoption of advanced analytics and machine learning solutions that improve business outcomes and decision making.
  • Establish frameworks to measure adoption, business impact, and value realization of Data Science investments.
  • Shape an organization known for technical excellence, innovation, accountability, and continuous learning.

What We're Looking For
  • 15+ years of progressive leadership experience in Data Science, Machine Learning, AI, Advanced Analytics, Statistical Modeling, or related quantitative disciplines.
  • Deep familiarity with gaming, digital product, media, or entertainment businesses preferred.
  • Experience leading enterprise Data Science organizations through Directors, Managers, and senior technical leaders.
  • Proven success building and scaling Data Science capabilities that enable production machine learning, AI, and advanced analytics solutions.
  • Experience defining enterprise Data Science operating models, governance frameworks, and model lifecycle practices that support the scalable adoption of advanced analytics, machine learning, and AI.
  • Experience evaluating emerging Data Science, AI, and machine learning technologies and converting innovation opportunities into practical business capabilities.
  • Outstanding executive communication, partner influence, and organizational leadership skills, able to build strong partnerships across business and technology functions.
  • Master's degree or PhD in Data Science, Statistics, Computer Science, Mathematics, Engineering, Economics, or a related quantitative field preferred; equivalent experience will also be considered.
Compensation Philosophy
We offer a comprehensive pay and benefits package designed to stay competitive in the market, support your wellbeing, and recognise your contribution to our success. Our approach is underpinned by a pay-for-performance belief in rewarding individual impact. Your specific compensation package will be determined by factors such as your skills, experience, qualifications, and location.
Depending on your role and location, you may be eligible for annual bonuses and incentives, health and wellbeing benefits, paid time off, retirement plans, insurance coverage, and other local or statutory benefits.
Specific details about compensation and benefits for this position will be discussed during the recruitment process.

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