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Google Colab Jobs (NOW HIRING)

Data Scientist

$110K - $117K/yr

... Google Colab for data modeling, processing, and automation. • Design and maintain data warehouse solutions to support advanced analytics and business intelligence. • Perform complex data ...

... Google Colab for interactive analysis and modeling. Additional Responsibilities & Preferred Qualifications: EOE, including disability/vets. The base pay for this role will depend on where you work ...

The candidate should be proficient in Python and comfortable working in notebook environments (e.g., Jupyter, Google Colab) with version-controlled, reproducible workflows. Working closely with ...

Machine Learning Engineer

San Jose, CA · On-site

$188 - $271/hr

Experience in Jupyter Notebooks and/or Google Colab for interactive analysis and modeling. Additional Responsibilities & Preferred Qualifications: EOE, including disability/vets. The base pay for ...

... Google Colab for interactive analysis and modeling. Additional Responsibilities & Preferred Qualifications: EOE, including disability/vets. The base pay for this role will depend on where you work ...

Hands-on experience with Python and Jupyter Notebook, Google Colab, or similar platforms * Demonstrated experience communicating technical concepts to business stakeholders and technical subject ...

Showing results 21-40

Google Colab information

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$24K

$77.7K

$172.5K

How much do google colab jobs pay per year?

As of Aug 20, 2026, the average yearly pay for google colab in the United States is $77,698.00, according to ZipRecruiter salary data. Most workers in this role earn between $34,500.00 and $112,500.00 per year, depending on experience, location, and employer.

What is Google Colab?

Google Colab, short for Google Colaboratory, is a free cloud-based platform that allows users to write and execute Python code through a web browser. It is especially popular for machine learning, data analysis, and education because it provides free access to GPUs and TPUs. Colab notebooks are similar to Jupyter notebooks and support easy sharing and collaboration. Users can also import data from Google Drive and other sources, making it a convenient tool for both beginners and professionals.

What is a Google Colab job?

A Google Colab job typically refers to tasks or projects performed using Google Colaboratory, a cloud-based Jupyter notebook environment. It is commonly used for machine learning, data analysis, and Python development without requiring local setup. Professionals working with Google Colab may include data scientists, AI researchers, and engineers leveraging GPU and TPU resources for computation.

What are some common challenges faced when working as a Google Colab specialist in a collaborative team environment?

As a Google Colab specialist, one common challenge is ensuring smooth collaboration when multiple team members are working on the same notebook, as version control can be tricky. Managing dependencies and ensuring consistent environments across users also requires careful setup, since Colab sessions can reset and lose installed packages. Additionally, dealing with Colab's resource limitations, such as session timeouts or GPU availability, can impact project timelines. Clear communication and structured workflows help mitigate these challenges and support efficient teamwork.

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

To thrive as a Google Colab Data Scientist, you need a strong foundation in Python programming, data analysis, and machine learning, typically supported by a degree in computer science or a related field. Familiarity with Google Colab, Jupyter Notebooks, TensorFlow, and data visualization libraries is essential. Strong problem-solving, communication, and collaboration skills help you effectively interpret data and share results with stakeholders. These skills enable efficient development and sharing of reproducible data science workflows in a collaborative, cloud-based environment.

What is the difference between Google Colab vs Data Scientist?

FeatureGoogle ColabData Scientist
Primary UseCloud-based platform for coding, collaboration, and machine learning experimentsAnalyzing data, building models, and deriving insights from data
Required SkillsPython, Jupyter notebooks, basic ML knowledgeStatistics, programming, data analysis, ML expertise
Work EnvironmentOnline, collaborative, flexibleOffice or remote, analytical and research-focused
CredentialsNone required, but programming skills neededDegree in data science, statistics, or related field

Google Colab is a tool used by data scientists for coding and experimentation, while a data scientist is a professional who analyzes data and builds models. Google Colab supports data science tasks but is not a job role itself. Understanding the differences helps in choosing the right tools and career path.

How do I get into Google Colab?

Google Colab is a cloud-based platform that allows users to run Python code in Jupyter notebooks. To access it, sign in with a Google account, navigate to colab.research.google.com, and create a new notebook or open existing ones. Basic knowledge of Python and familiarity with Jupyter notebooks are helpful for using Colab effectively.
More about Google Colab jobs

What are the most commonly searched types of Google Colab jobs?

The most popular types of Google Colab jobs are:

Infographic showing various Google Colab job openings in the United States as of August 2026, with employment types broken down into 80% Full Time, and 20% Contract. Highlights an 60% In-person, and 40% Remote job distribution, with an average salary of $77,698 per year, or $37.4 per hour.

$110K - $117K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 11 days ago


Owens & Minor rating

6.6

Company rating: 6.6 out of 10

Based on 56 frontline employees who took The Breakroom Quiz

271st of 365 rated logistics


Job description

Owens & Minor is a global healthcare solutions company providing essential products, services and technology solutions that support care delivery in leading hospitals, health systems and research centers around the world. For over 140 years, Owens & Minor has delivered comfort and confidence behind the scenes, so healthcare stays at the forefront, helping to make each day better for the hospitals, healthcare partners, and communities we serve. Powered by more than 14,000 teammates worldwide, Owens & Minor exists because every day, everywhere, Life Takes Care™.
Global Reach with a Local Touch
  • 140+ years serving healthcare
  • Over 14,000 teammates worldwide
  • Serving healthcare partners in 80 countries
  • Manufacturing facilities in the U.S., Honduras, Mexico, Thailand and Ireland
  • 40+ distribution centers
  • Portfolio of 300 propriety and branded product offerings
  • 1,000 branded medical product suppliers
  • 4,000 healthcare partners served

Benefits
  • Comprehensive Healthcare Plan - Medical, dental, and vision plans start on day one of employment for full-time teammates.
  • Educational Assistance - We offer educational assistance to all eligible teammates enrolled in an approved, accredited collegiate program.
  • Employer-Paid Life Insurance and Disability - We offer employer-paid life insurance and disability coverage.
  • Voluntary Supplemental Programs - We offer additional options to secure your financial future including supplemental life, hospitalization, critical illness, and other insurance programs.
  • Support for your Growing Family - Adoption assistance, fertility benefits (in medical plan) and parental leave are available for teammates planning for a family.
  • Health Savings Account (HSA) and 401(k) - We offer these voluntary financial programs to help teammates prepare for their future, as well as other voluntary benefits.
  • Paid Leave - In addition to sick days and short-term leave, we offer holidays, vacation days, personal days, and additional types of leave - including parental leave.
  • Well-Being - Also included in our offering is a Teammate Assistance Program (TAP), Calm Health, Cancer Resources Services, and discount programs - all at no cost to you.
  • The anticipated salary range for this position is $110,000- $117,000 USD Annual. The actual compensation offered may vary based on job related factors such as experience, skills, education and location

Job Description:
We are seeking a highly skilled Data Scientist with a strong background in machine learning, data engineering, and model optimization. The ideal candidate should be proficient in Python, PySpark, and SQL, experienced in time series forecasting, feature engineering, and data model performance evaluation, and capable of working with large-scale data integration projects across various domains.
A large part of this role involves building machine learning models that not only meet but exceed user expectations, driving measurable value for the business. The candidate will need to have a strong grasp of data model optimization, feature engineering, and model evaluation metrics to ensure high-performance solutions.
This role also requires experience with cloud platforms, ETL tools, data transformation processes, and working with structured and unstructured data. While not required, familiarity with object-oriented programming languages (C#, Java, JavaScript) is a plus. Strong communication skills are essential for collaborating with cross-functional teams and presenting findings effectively.
Key Responsibilities:
• Develop and optimize machine learning models with a focus on time series forecasting and predictive analytics.
• Perform feature engineering and data model optimization to enhance model accuracy and efficiency.
• Continuously evaluate model performance using metrics such as MAPE, RMSE, R², and adjust strategies accordingly.
• Build and implement data pipelines using PySpark, SQL, and cloud-based solutions for seamless data integration.
• Work on large-scale data integration projects, leveraging tools such as Boomi, SnapLogic, SSIS, or Palantir to extract, transform, and load data.
• Utilize Palantir Foundry, Google Cloud, AutoAI, and Google Colab for data modeling, processing, and automation.
• Design and maintain data warehouse solutions to support advanced analytics and business intelligence.
• Perform complex data transformations using SQL queries and data objects to support AI/ML-driven initiatives.
• Collaborate closely with business stakeholders to ensure models align with user expectations and business objectives.
• Deploy, monitor, and continuously improve machine learning models in production environments.
• Communicate technical findings and insights effectively to both technical and non-technical audiences.
Required Skills & Qualifications:
• Proficiency in Python, PySpark, and SQL for data analysis, feature engineering, and model development.
• Expertise in time series forecasting models, including ARIMA, Prophet, LSTMs, and ML-based approaches.
• Strong experience in data model optimization, feature engineering, and performance evaluation.
• Deep understanding of ML model evaluation metrics and best practices in improving model accuracy.
• Hands-on experience in data engineering, working on data pipelines, ETL, and data transformation projects.
• Experience using Boomi, SnapLogic, SSIS, or Palantir for data integration.
• Proficiency in cloud computing, particularly Google Cloud (BigQuery, Vertex AI, Cloud Functions, etc.).
• Experience with Palantir Foundry for data processing, analysis, and visualization.
• Ability to optimize and query large-scale datasets using data lakes and relational databases.
• Familiarity with AutoAI for automated model selection and hyperparameter tuning.
• Experience with Google Colab for collaborative machine learning development.
• Excellent problem-solving and communication skills, with the ability to convey complex concepts to business stakeholders.
Preferred Qualifications:
• Experience with MLOps for continuous deployment, monitoring, and retraining of ML models.
• Knowledge of business intelligence and reporting tools for data visualization.
• Background in supply chain, logistics, or operational forecasting.
• Experience in both batch and real-time data processing architectures.
• Ability to optimize SQL queries and data transformations for performance improvements.
• Familiarity with object-oriented programming languages such as C#, Java, or JavaScript (not required but beneficial).
If you feel this opportunity could be the next step in your career, we encourage you to apply. This position will accept applications on an ongoing basis.
Owens & Minor is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, national origin, sex, sexual orientation, genetic information, religion, disability, age, status as a veteran, or any other status prohibited by applicable national, federal, state or local law.

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