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Manager Data Scientist Jobs in Nevada (NOW HIRING)

Jobtailor

Staff Data Scientist

Carson City, NV · On-site

$180 - $260/hr

Highlighting experience in mentoring teams, managing complex data challenges, and collaborating ... Data Science Methodologies * Mentoring Data Scientists * Collaboration Across Teams ATS ...

MOREgroup

Manager, Data Science & Services

Reno, NV

Develop and maintain data solutions that support reporting, business intelligence, data science ... Lead and manage offshore teams of developers, analysts, engineers, and administrators to support ...

New

MOREgroup

Manager, Data Science & Services

Reno, NV · On-site

Develop and maintain data solutions that support reporting, business intelligence, data science ... Lead and manage offshore teams of developers, analysts, engineers, and administrators to support ...

New

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All JobsData Scientist JobsManager Data Scientist JobsManager Data Scientist Jobs in Nevada

Manager Data Scientist information

See Nevada salary details

$46.8K

$168K

$248K

How much do manager data scientist jobs pay per year?

As of Aug 23, 2026, the average yearly pay for manager data scientist in Nevada is $168,039.00, according to ZipRecruiter salary data. Most workers in this role earn between $135,900.00 and $173,100.00 per year, depending on experience, location, and employer.

What is a manager data scientist?

Manager Data Scientists are professionals who oversee data science teams and projects within an organization. They combine advanced analytical skills with leadership abilities to guide data scientists, set project priorities, and ensure data-driven strategies align with business goals. In addition to technical expertise in data modeling, machine learning, and analytics, they are responsible for mentoring team members, managing resources, and communicating insights to stakeholders. Their role bridges the gap between technical execution and strategic decision-making.

What are the key skills and qualifications needed to thrive as a manager data scientist?

To thrive as a Manager Data Scientist, you need expertise in statistical analysis, machine learning, data modeling, and a relevant degree such as in computer science, mathematics, or statistics. Familiarity with tools like Python, R, SQL, cloud platforms (e.g., AWS, Azure), and experience with data visualization software and project management methodologies are commonly required. Strong leadership, effective communication, and the ability to mentor and guide teams are vital soft skills in this role. These competencies ensure successful project delivery, drive data-driven business decisions, and foster a productive, innovative team environment.

How does a manager data scientist typically collaborate with cross-functional teams to drive business outcomes?

As a Manager Data Scientist, you will work closely with teams such as engineering, product management, and business stakeholders to ensure data-driven solutions align with company goals. This collaboration often involves translating complex analytical findings into actionable insights, setting project priorities, and managing expectations. You will also facilitate communication between data scientists and non-technical teams to foster understanding and ensure successful project delivery. Building strong relationships and promoting a culture of data-driven decision-making are essential aspects of the role.

What is the difference between Manager Data Scientist vs Data Scientist?

AspectManager Data ScientistData Scientist
Required CredentialsBachelor's or Master's in Data Science, Statistics, or related field; leadership experienceBachelor's or Master's in Data Science, Statistics, or related field
Work EnvironmentLeads teams, manages projects, collaborates with stakeholdersAnalyzes data, develops models, reports findings
Employer & Industry UsageUsed in organizations with data teams, tech, finance, healthcareFound across industries, entry to mid-level roles

The main difference is that a Manager Data Scientist oversees data teams and projects, focusing on leadership and strategic planning, while a Data Scientist primarily conducts data analysis and model development. The manager role involves more coordination, mentorship, and stakeholder communication, whereas the data scientist role emphasizes technical skills and hands-on analysis.

What are the most commonly searched types of Data Scientist jobs in Nevada?

The most popular types of Data Scientist jobs in Nevada are:

What cities in Nevada are hiring for Manager Data Scientist jobs?

Cities in Nevada with the most Manager Data Scientist job openings:

Manager Data Scientist jobs near you
Infographic showing various Manager Data Scientist job openings in Nevada as of August 2026, with employment types broken down into 86% Full Time, 12% Part Time, and 2% Contract. Highlights an 83% Physical, 2% Hybrid, and 15% Remote job distribution, with an average salary of $168,039 per year, or $80.8 per hour.

Senior Data Scientist

Ceasars Entertainment

Las Vegas, NV

Full-time

Posted 17 days ago

Caesars Entertainment rating

6.4

Company rating: 6.4 out of 10

Based on 255 frontline employees who took The Breakroom Quiz

107th of 164 rated casinos

Job description

Join our Sportsbook team as a Senior Data Scientist responsible for end-to-end model development-designing, deploying, and refining predictive and pricing models that power our real-time odds, trading decisions, and risk management.

At Caesars Digital, We Don't Just Play the Game - We Set the Standard.

As a proud part of Caesars Entertainment, the world's premier gaming company with more than 80 years of sports betting leadership, Caesars Digital is Blazing The Trail in digital innovation, customer experience and industry excellence.

We believe every Team Member should be treated like royalty because We Are All Caesars. This guiding principle fuels our commitment to delivering legendary service and creating unforgettable experiences for our customers.

From cutting-edge digital platforms including Caesars Sportsbook, Caesars Palace Online, Horseshoe Online Casino and Caesars Racebook, to the continuing expansion of our retail footprint and our William Hill legacy, along with powerhouse partnerships across sports and entertainment, we're building something extraordinary. And we want you to be part of it.

Ready to make your mark on the Empire?

Explore our open roles and discover how you can help shape the future of gaming.

Join us. Blaze the Trail. Because at Caesars Digital, We Are All Caesars.

Qualifications

  • Degree in Statistics, Mathematics, Computer Science, Data Science, or similar.
  • 5+ years in data science or ML with at least 2+ years focused on sportsbook, gaming, or financial trading models.
  • Deep knowledge of probability, statistical methods, and advanced ML techniques.
  • Proficient in Python (NumPy, pandas, scikit-learn, etc). 
  • Experience with automated model deployment and testing frameworks. 
  • Strong SQL and data pipeline understanding
  • Understanding of betting mechanics-odds formulation, overround, liability, in-play dynamics.
  • Excellent problem-solving, communication, and collaboration skills. Proven track record of influencing product/trading decisions.

Nice to Have

  • Avid sports fan
  • Prior roles at leading sportsbooks
  • Experience building sports models
  • Experience programming in Go
  • Experience Sports Betting

Key Responsibilities

  • Design and refine statistical and machine learning models to predict outcome probabilities and set accurate prices across a wide range of sports betting markets
  • Extract and engineer features from live feeds (e.g., player stats, team form, weather, betting flow), ensuring data quality and integrity. 
  • Continuously track model behavior through KPIs-P&L, hold, liability, and recalibrate based on findings
  • Work closely with Trading, Product, and Engineering teams to translate business goals into model requirements and ensure successful rollouts. 
  • Stay up-to-date with sports analytics, statistical methods, and advanced machine learning; evaluate new methods to keep our models best-in-class. 
  • Guide junior data scientists in model design, experiments, and best practices. 
  • Collaborate with engineering to deploy models in production via APIs or model engines, implementing automated testing for accuracy, performance benchmarking, and drift monitoring. 
  • Translate model insights into clear recommendations for trading strategies, risk limits, and event-level pricing decisions. 
  • Ability to uphold and demonstrate the highest level of integrity in all situations and recognize standards required by a regulated business

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