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Google Internship Data Science Jobs in Colorado (NOW HIRING)

... Google Cloud Platform (GCP) stack, ensuring models are automated, monitored, and scalable. • Establishing data science workflows, standards, and code repositories from scratch in a new regional ...

As the Data Science Team Leader, you will be a critical part of our expanding global data ... Hands-on experience with Google Cloud Platform (GCP), ideally including the Vertex AI ecosystem ...

Data Science Team Leader

Denver, CO · On-site

$155K - $165K/yr

As the Data Science Team Leader, you will be a critical part of our expanding global data ... Hands-on experience with Google Cloud Platform (GCP), ideally including the Vertex AI ecosystem ...

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 ...

Data Scientist

Colorado Springs, CO · On-site

$155K - $190K/yr

Google Data Analytics Professional Certificate; IBM Data Science Professional Certification. Qualifications Minimum Experience: Citizenship: Must be a US citizen Clearance: Must have and be able to ...

Data Scientist

Colorado Springs, CO · On-site

$155 - $190/hr

Google Data Analytics Professional Certificate; IBM Data Science Professional Certification. Qualifications MinimumExperience: Citizenship: Must be a US citizen Clearance: Must have and be able to ...

Data Science Team Leader

Denver, CO · On-site

$155K - $165K/yr

As the Data Science Team Leader, you will be a critical part of our expanding global data ... Hands-on experience with Google Cloud Platform (GCP), ideally including the Vertex AI ecosystem ...

Environmental Data Scientist

Boulder, CO · On-site +1

$75K - $105K/yr

A working sense of geospatial data science, including experience with GIS tooling and spatial datasets (e.g., R, ArcGIS, QGIS, Google Earth Engine). * Comfort thinking structurally about data schemas ...

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Google Internship Data Science information

What are the key skills and qualifications needed to thrive as a Google data science intern, and why are they important?

To thrive as a Google Data Science Intern, you need a solid background in statistics, programming (such as Python or R), and data analysis, typically supported by current enrollment in a relevant degree program. Familiarity with tools like SQL, TensorFlow, and data visualization platforms is commonly expected, along with experience in machine learning frameworks. Strong problem-solving abilities, effective communication, and collaboration skills help interns contribute meaningfully to cross-functional teams. These skills are essential to analyze complex datasets, deliver actionable insights, and succeed in Google's fast-paced, innovative environment.

What types of projects does a data science intern typically work on during a Google internship?

Data Science interns at Google often collaborate on high-impact projects alongside full-time data scientists and engineers. Projects may include analyzing large datasets to identify trends, building machine learning models, or developing data-driven solutions for products and services. Interns are encouraged to contribute ideas, participate in code reviews, and present findings to their teams. This hands-on experience allows interns to gain exposure to Google's tools and methodologies, while also building a strong foundation for future roles in data science.

What is a Google internship in data science?

A Google Internship in Data Science is a temporary, paid position where students or recent graduates work with Google's data science teams. Interns are involved in analyzing large datasets, building machine learning models, and providing insights to improve Google products and services. The internship offers hands-on experience, mentorship, and exposure to real-world data science challenges in a leading tech company. Applicants typically need strong analytical skills, proficiency in programming languages like Python or R, and a background in statistics or computer science.

What is the difference between Google Internship Data Science vs Google Data Analyst Internship?

AspectGoogle Internship Data ScienceGoogle Data Analyst Internship
Required SkillsProgramming (Python, R), statistics, machine learning, data modelingData analysis, SQL, Excel, visualization tools
Work EnvironmentCollaborative, research-focused, technical projectsBusiness-oriented, reporting, data interpretation
Industry UsageResearch, product development, machine learning modelsBusiness insights, performance metrics, reporting

Google Internship Data Science roles focus on developing machine learning models and advanced analytics, requiring programming and statistical skills. In contrast, Google Data Analyst Internships emphasize data interpretation, reporting, and visualization for business decisions. Both roles are valuable within Google's data ecosystem but serve different functions based on technical depth and business application.

What job categories do people searching Google Internship Data Science jobs in Colorado look for?

The top searched job categories for Google Internship Data Science jobs in Colorado are:

What cities in Colorado are hiring for Google Internship Data Science jobs?

Cities in Colorado with the most Google Internship Data Science job openings:

Infographic showing various Google Internship Data Science job openings in Colorado as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 13% Part Time, and 4% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.

Data Science Team Lead/Manager

Bet365

Denver, CO • On-site

Full-time

Posted 22 days ago


Bet365 rating

8.9

Company rating: 8.9 out of 10

Based on 14 frontline employees who took The Breakroom Quiz

2nd of 15 rated gambling companies


Job description

hackajob is collaborating with Bet365 to connect them with exceptional professionals for this role.

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, and AgentOps Team Lead within the wider 
US Data team, while maintaining strong operational alignment and knowledge sharing with our 
established UK-based Data Science team.  

Main Responsibilities: 
• 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. 
• Partnering closely with the Data Team Lead, Data Product Lead, and AgentOps Team Lead 
to align data science initiatives with product roadmaps and platform capabilities. 
• Collaborating regularly with our UK-based Data Science team of technical excellence to 
share methodology, align on standards, and leverage global technical capabilities. 
• Translating complex, ambiguous business questions into clear data science initiatives, 
delivering measurable business value through rapid prototyping and deployment cycles. 
• Collaborating with Machine Learning Engineers to champion the adoption of 
robust MLOps practices on our Google Cloud Platform (GCP) stack, ensuring models are 
automated, monitored, and scalable. 
• Establishing data science workflows, standards, and code repositories from scratch in a 
new regional office. 
The skills and experience to help you perform in the role: 
• Proven experience working in a fast-paced, agile, or startup-like environment. You must 
have a demonstrated passion for “getting things done” and delivering value iteratively. 
• Prior experience mentoring, coaching, or leading data scientists or engineers while 
remaining active in code development. 
• A strong track record of designing, building, deploying, and maintaining machine learning 
models in production environments 
• Superior communication 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 
Google BigQuery.  
• Hands-on experience with Google Cloud Platform (GCP), ideally including the Vertex AI 
ecosystem (Pipelines, Workbench, Endpoints). 
• MSc or 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-driven architectures (e.g., Kafka). 


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