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Data Science Jobs in Colorado (NOW HIRING)

As the Data Science Team Leader, you will be a critical part of our expanding global data organization. You will remain deeply technical and actively involved in writing code, building models, and ...

Required : • Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 1+ year(s) data-science experience (e.g ...

As the Data Science Team Leader, you will be a critical part of our expanding global data organization. You will remain deeply technical and actively involved in writing code, building models, and ...

As the Data Science Team Leader, you will be a critical part of our expanding global data organization. You will remain deeply technical and actively involved in writing code, building models, and ...

New

Data Scientist

Boulder, CO · On-site

$130K - $160K/yr

Master's or PhD in Data Science, Statistics, or related field. * 5-8 years of data science experience. * Expertise in Python, SQL, and machine learning frameworks. * Strong analytical and ...

Qualifications Required Skills: * 5+ years in Data Science. * Strong Python coding/scripting Skills. * AWS CI/CD exposure. * Ability to build models that can drive value of data. Deploy the data into ...

AI and Data Science Engineer III

Denver, CO · On-site

$117K - $141K/yr

AI Data Science Engineer III Our Deloitte Human Capital team transforms technology platforms, drives innovation, and helps make a significant impact on our clients' success. We are hiring a Senior ...

Qualifications Required Skills: * 5+ years in Data Science. * Strong Python coding/scripting Skills. * AWS CI/CD exposure. * Ability to build models that can drive value of data. Deploy the data into ...

Senior Data Scientist

Denver, CO · On-site

$135K - $150K/yr

The data science team is at the forefront of driving business decisions, we are now scaling our impact with a focus on automation and advanced MLOps practices on Google Cloud. This is a key technical ...

The data science team is at the forefront of driving business decisions, we are now scaling our impact with a focus on automation and advanced MLOps practices on Google Cloud. This is a key technical ...

The data science team is at the forefront of driving business decisions, we are now scaling our impact with a focus on automation and advanced MLOps practices on Google Cloud. This is a key technical ...

$49K/yr

Mathematics, statistics, computer science, data science or field directly related to the position. The degree must be in a major field of study (at least at the baccalaureate level) that is ...

Stay up to date with the latest trends and technologies in data science and machine learning. * Ability to work independently and collaborate as part of a team * Effective written and verbal ...

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Data Science information

See Colorado salary details

$39.4K

$129.1K

$206.6K

How much do data science jobs pay per year?

As of Jun 21, 2026, the average yearly pay for data science in Colorado is $129,062.00, according to ZipRecruiter salary data. Most workers in this role earn between $103,600.00 and $143,000.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Data Scientist, and why are they important?

To thrive as a Data Scientist, you need a strong background in statistics, programming (often Python or R), and data analysis, usually supported by a degree in a quantitative field. Familiarity with machine learning libraries (like scikit-learn or TensorFlow), big data tools (such as Hadoop or Spark), and data visualization platforms is typically required. Critical thinking, problem-solving, and effective communication are vital soft skills for translating complex data insights into actionable business strategies. These skills and qualities are essential for extracting value from data, driving informed decisions, and effectively collaborating with multidisciplinary teams.

Is 40 too late for data science?

Data science is a field open to individuals of all ages, and many professionals transition into it later in their careers. Success often depends on acquiring relevant skills such as programming, statistics, and machine learning, which can be learned through online courses, bootcamps, or degrees regardless of age.

What are some common challenges faced by data scientists when working with real-world datasets?

Data scientists often encounter challenges such as missing or inconsistent data, unstructured formats, and noisy information in real-world datasets. Cleaning and preprocessing data to ensure its quality can be time-consuming but is critical for building accurate models. Additionally, data scientists may work closely with domain experts and other team members to better understand the data's context and ensure their analyses align with business objectives. Overcoming these challenges requires strong problem-solving skills and effective collaboration within cross-functional teams.

Is AI replacing data scientists?

AI is transforming the role of data scientists by automating routine tasks such as data cleaning and basic analysis, but it does not replace the need for skilled professionals to interpret complex data, develop models, and make strategic decisions. Data scientists with expertise in programming, statistical analysis, and machine learning remain essential for designing and deploying AI solutions effectively.

What is data science?

Data science is an interdisciplinary field that uses scientific methods, algorithms, and systems to extract insights and knowledge from structured and unstructured data. It combines skills from statistics, computer science, and domain expertise to analyze and interpret complex data sets. Data scientists work with large amounts of data to identify patterns, make predictions, and help organizations make data-driven decisions.

What is the difference between Data Science vs Data Analyst?

AspectData ScienceData Analyst
Required skillsStatistics, programming (Python, R), machine learningData visualization, SQL, basic statistics
Work environmentDeveloping models, predictive analytics, researchReporting, data cleaning, descriptive analysis
Tools usedPython, R, Jupyter, TensorFlowExcel, SQL, Tableau, Power BI
Industry usageTech, finance, healthcare, e-commerceRetail, marketing, finance, healthcare

Data Science and Data Analyst roles often overlap but differ mainly in scope. Data Scientists focus on building predictive models and advanced analytics, requiring programming and machine learning skills. Data Analysts primarily handle data cleaning, reporting, and visualization. Both roles are essential in data-driven industries, but Data Science is more technical and research-oriented, while Data Analysis emphasizes interpreting data for business insights.

What jobs are there in data science?

Data science offers a variety of roles including Data Scientist, Data Analyst, Machine Learning Engineer, Data Engineer, and Business Intelligence Analyst. These positions typically require skills in programming, statistics, and data visualization tools, and may involve working with large datasets, predictive modeling, and data-driven decision making.

What Does a Data Scientist Do?

As a Data Scientist, you are qualified to work in such diverse fields as research and development, politics, advertising and marketing, technology, healthcare, government, and higher education as well as multiple others. In general, your duties and responsibilities will be to compile and analyze relevant statistics and turn those numbers into algorithms that reveal insights that can be used by other researchers in their areas of study. Data Science can reveal things like consumer buying habits or the likelihood of success for a course of action. Other duties might vary, depending on your unique field of specialty. Related areas in which a Data Scientist might wish to focus include work as a Data Analyst, Machine Learning Engineer, and Project Manager.

What jobs does a data scientist do?

A data scientist analyzes large datasets to extract insights, build predictive models, and support decision-making. They use programming languages like Python or R, employ statistical techniques, and often work with machine learning algorithms to solve complex problems across various industries.
What are the most commonly searched types of Data Science jobs in Colorado? The most popular types of Data Science jobs in Colorado are:
What cities in Colorado are hiring for Data Science jobs? Cities in Colorado with the most Data Science job openings:
Infographic showing various Data Science job openings in Colorado as of June 2026, with employment types broken down into 1% As Needed, 86% Full Time, 11% Part Time, and 2% Contract. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution, with an average salary of $129,062 per year, or $62 per hour.

Data Science Team Leader

bet365

Denver, CO

$165K/yr

Full-time

Posted 3 days ago


Bet365 rating

9.7

Company rating: 9.7 out of 10

Based on 6 frontline employees who took The Breakroom Quiz

1st of 15 rated gambling companies


Job description

Company Description

At bet365, we're one of the world's leading online gambling companies, revolutionising the industry since 2000. Founded by Denise Coates CBE, we now employ over 9,000 people and serve over 100 million customers in 27 languages. Our focus on In-Play betting has solidified our market-leading position, offering an unmatched experience across 96 sports and 700,000 streaming events. With over 750 concurrent sporting fixtures at peak and more live sports streamed than anyone else in Europe, we handle over 6 billion HTTP requests daily and process more than 2 million bets per hour at peak.

We empower our employees to push boundaries and explore new ideas, cultivating a culture that celebrates and rewards creativity. This offers employees a wealth of opportunities for growth, giving them the opportunity to make a real impact in the world of online gambling. As a forward-thinking company, we're breaking new ground in software innovation too, redefining what's possible for our customers worldwide.

Job Description

This is an exceptional, hands-on, player/coach opportunity to establish, shape, and lead our Data Science capability in the United States. As the Data Science Team Leader, you will be a critical part of our expanding global data organization.

You will remain deeply technical and actively involved in writing code, building models, and executing machine learning solutions, while simultaneously mentoring and growing a high-performing team of US-based Data Scientists and Machine Learning Engineers.

We are intentionally recruiting for a specific kind of professional: someone with a startup mindset who thrives in fast-paced environments, possesses a strong bias for action, and values execution over theoretical complexity. To succeed, you must be a pragmatic problem solver who enjoys getting their hands dirty while building scalable, production-grade solutions.

Excellent stakeholder management is paramount. You will work as a key collaborative partner alongside the US Data Team Lead, Data Product Lead, andAgentOpsTeam Lead within the wider US Data team, while maintaining strong operational alignment and knowledge sharing with our established UK-based Data Science team.

The listed salary for this position is $165,000 annually.

Qualifications
  • Provenexperience working in a fast-paced, agile, or startup-like environment. You must have a demonstrated passion for "getting things done" and delivering value iteratively. 
  • Priorexperience mentoring, coaching, or leading data scientists or engineers while remaining active in code development. 
  • Astrong track record of designing, building, deploying, and maintaining machine learning models in production environments 
  • Superiorcommunication skills with the ability to build strong cross-functional relationships and translate technical concepts into business outcomes for both technical and non-technical audiences. 
  • Exceptional programming skills in Python and deep expertise in data science libraries (Scikit-learn, Pandas, NumPy,XGBoost, etc.). 
  • Advanced SQL proficiency for querying and manipulating large datasets, preferably within GoogleBigQuery. 
  • Hands-on experience with Google Cloud Platform (GCP), ideally including the Vertex AI ecosystem (Pipelines, Workbench, Endpoints). 
  • MScor PhD in a quantitative discipline (Computer Science, Statistics, Mathematics, Engineering) or equivalent practical industry experience. 
  • Familiarity with containerization (Docker, Kubernetes) and CI/CD principles for machine learning. 
  • Experience with real-time stream processing or event-drivenarchitectures(e.g., Kafka).
Additional Information
  • In this hands-on role you will devise, code, and deploy AI, machine learning and predictive models, leading by example in technical execution and code quality. This is not a pure people-management role. 
  • Building, mentoring, and guiding a pragmatic, delivery-focused team of Junior Data Scientists and Machine Learning Engineers, fostering a culture of rapid iteration, continuous learning, and software engineering discipline. 
  • Partneringclosely with the Data Team Lead, Data Product Lead, andAgentOpsTeam Lead to align data science initiatives with product roadmaps and platform capabilities. 
  • Collaboratingregularly with our UK-based Data Science team of technical excellence to share methodology, align on standards, and leverage global technical capabilities. 
  • Translatingcomplex, ambiguous business questions into clear data science initiatives, delivering measurable business value through rapid prototyping and deployment cycles. 
  • Collaboratingwith Machine Learning Engineers to champion the adoption of robustMLOpspractices on our Google Cloud Platform (GCP) stack, ensuring models are automated, monitored, and scalable. 
  • Establish data science workflows, standards, and code repositories from scratch in a new regional office.

bet365 provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws.