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Google Colab Jobs (NOW HIRING)

Mercor

Data Science Expert - AI/ML

San Francisco, CA · Remote

$60 - $90/hr

Author clear, reproducible reference analyses in Jupyter Notebooks or Google Colab . * Build tasks for fair comparison between analytical approaches, backed by spot checks and recommendations.

Weekday AI

STEM Researcher - Computational Fields

$60 - $90/hr

Working knowledge of Git , integrated development environments (IDEs), and notebook platforms such as Jupyter or Google Colab . * Experience with AI evaluation, benchmark development, AI training, or ...

Halyard Health

Data Scientist

Glen Allen, VA · On-site

$110 - $117/hr

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 ...

Owens & Minor

Data Scientist

$110K - $117K/yr

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 ...

Halyard Health

$110 - $117/hr

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

PayPal

Machine Learning Engineer

San Jose, CA · On-site

$188 - $271/hr

... 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 and ...

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

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What job categories do people searching Google Colab jobs look for?

The top searched job categories for Google Colab jobs are:

Google Colab jobs near you
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.

Fixed Income Product Manager

Cantor Fitzgerald Securities

Manhattan, NY • On-site

Full-time

Re-posted 9 days ago

Job description

The Fixed Income Product Manager will act as the bridge between business stakeholders, broking desks, and technology teams. The successful candidate will help identify, define, and deliver platform enhancements that drive revenue growth, expand market coverage, and ensure regulatory compliance.

  • Deep understanding of Fixed Income products including Treasuries, Gilts, EGBs, TIPS/Linkers, and Corporate Bonds.
  • Strong grasp of derivative instruments such as Credit Default Swaps (CDS) and Interest Rate Swaps (IRS), OIS, FRAs, Caps/Floors, and Swaptions.
  • Excellent understanding of price, yield-to-maturity, and DV01 concepts and their underlying calculations.
  • Familiarity with structured trades and packages (switches, flies, basis, gadgets, spread switches) and how they are priced and settled.
  • Knowledge of trading protocols such as Central Limit Order Books (CLOB) and auction mechanisms.
  • (Optional) Understanding of implied trading and legging strategies.
Technical Skills
  • Advanced Excel proficiency.
  • Working knowledge of SQL for querying databases (Oracle, Sybase, NoSQL).
  • Ability to conduct data analysis in Python using frameworks such as Pandas and Matplotlib (in Jupyter Notebook or Google Colab).
  • Ability capture requirements in Confluence and Jira
  • Familiarity with test automation and ability to guide the QA team on test scenarios 
  • Collaborate with business stakeholders to identify new feature opportunities that enhance revenue potential, market reach, and compliance.
  • Translate business requirements into clear, actionable system requirements.
  • Liaise between broking desks, developers, and QA teams to ensure successful implementation and rollout of solutions.
  • Support QA during testing and coordinate User Acceptance Testing (UAT) with end users to ensure timely sign-offs.

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