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Data Scientist Google Jobs (NOW HIRING)

The data science team is at the forefront of driving business decisions, we are now scaling our ... Extensive hands-on experience with Google Cloud Platform (GCP), including building and automating ...

The data science team is at the forefront of driving business decisions, we are now scaling our ... Extensive hands-on experience with Google Cloud Platform (GCP), including building and automating ...

Data Scientist

Mclean, VA

$125K - $160K/yr

Databricks Data Scientist Associate, AWS ML Specialty, Azure Data Scientist Associate, Google Professional Data Engineer. About steampunk Steampunk relies on several factors to determine salary ...

Data Scientist Job Type: Fulltime Job Location: Santa Clara, CA Work Schedule: Hybrid 4 days onsite ... Knowledge of cloud platforms (e.g., AWS, Google Cloud Platform, Azure). * Experience with data ...

... Google, Amazon, Apple, Meta, LinkedIn, Coinbase, Square, and Goldman Sachs. Hang raised a $16 ... About the Role As our first Data Scientist, you will leverage data to drive insights and strategies ...

Data Scientist

Mclean, VA · On-site

$125K - $160K/yr

Databricks Data Scientist Associate, AWS ML Specialty, Azure Data Scientist Associate, Google Professional Data Engineer. About steampunk Steampunk relies on several factors to determine salary ...

... ML / Google Cloud Platform Vertex AI), MLflow, and Docker. 4. Strong experience with SQL and ... data science and AI space, implement them, and share learnings with other team members.

Data Scientist

Santa Cruz, CA · Remote

$130K - $170K/yr

Experience with Amazon Web Services (AWS) or Google Cloud * Experience with C++ is a plus ... Experience applying data science and machine learning to real-world problems * Bachelor's degree or ...

Data Scientist Iv Location- Basking Ridge, NJ (Hybrid) 8 days/month in office (typically 2 days a ... Expertise in PowerPoint/Google slides presentation design and deck creation Strong executive ...

Overview Data Scientist McLean, VA TS/SCI with Poly At Bcore, our strength comes from how we ... Solid understanding of cloud platforms (AWS, Azure, or Google Cloud) and their data services.

Data Scientist

Mclean, VA

$125K - $160K/yr

Databricks Data Scientist Associate, AWS ML Specialty, Azure Data Scientist Associate, Google Professional Data Engineer. Steampunk relies on several factors to determine salary, including but not ...

Data Scientist

Mclean, VA

$125K - $160K/yr

Databricks Data Scientist Associate, AWS ML Specialty, Azure Data Scientist Associate, Google Professional Data Engineer. Steampunk relies on several factors to determine salary, including but not ...

Data Scientist - IV Location: Irving, TX (Hybrid) Duration: Long term contract Responsibilities ... Google Cloud Platform) and services (Big Query, google cloud storage, Cloud SQL, Vector Search and ...

Data Scientist

Mclean, VA

$125K - $160K/yr

Databricks Data Scientist Associate, AWS ML Specialty, Azure Data Scientist Associate, Google Professional Data Engineer. About steampunk Steampunk relies on several factors to determine salary ...

Data Scientist

Mclean, VA

$125K - $160K/yr

Databricks Data Scientist Associate, AWS ML Specialty, Azure Data Scientist Associate, Google Professional Data Engineer. About steampunk Steampunk relies on several factors to determine salary ...

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Data Scientist Google information

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$37.5K

$122.7K

$196.5K

How much do data scientist google jobs pay per year?

As of Jun 23, 2026, the average yearly pay for data scientist google in the United States is $122,738.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,500.00 and $136,000.00 per year, depending on experience, location, and employer.

How do I get into Google data scientist?

To become a data scientist at Google, candidates typically need a strong background in computer science, statistics, or related fields, along with experience in machine learning, data analysis, and programming languages like Python or R. A relevant advanced degree such as a master's or PhD is often preferred, and familiarity with tools like TensorFlow and big data platforms can be advantageous. Strong problem-solving skills, a portfolio of projects, and experience with large-scale data are also important for the application process.

How do Data Scientists at Google typically collaborate with cross-functional teams to deliver impactful projects?

At Google, Data Scientists frequently work alongside engineers, product managers, UX researchers, and business analysts to translate complex data insights into actionable product improvements. Collaboration often involves regular meetings to align on project goals, brainstorming sessions to identify potential data-driven solutions, and iterative feedback cycles to refine models or analyses. Open communication and a collaborative mindset are key, as Data Scientists are expected to clearly articulate findings to both technical and non-technical stakeholders, ensuring their work drives meaningful business outcomes.

Is it difficult to get hired at Google?

Getting hired as a Data Scientist at Google is competitive due to high standards for technical skills, including proficiency in programming, data analysis, and machine learning. Candidates typically need strong educational backgrounds, relevant experience, and a solid portfolio or projects to succeed in the interview process.

Can I get a job in Google as a data scientist?

Data Scientist roles at Google require strong skills in statistics, machine learning, and programming languages like Python or R. Candidates typically need a relevant degree, such as a master's or Ph.D., and experience with data analysis tools and large datasets. The hiring process includes technical interviews and assessments of problem-solving abilities.

Is 30 too late for data science?

Data scientists can successfully enter the field at age 30 or older, as skills in programming, statistics, and machine learning are more important than age. Many professionals transition into data science from different backgrounds, and continuous learning through online courses and certifications can facilitate this career change.

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

To thrive as a Data Scientist at Google, you need strong expertise in statistics, machine learning, data analysis, and a relevant degree such as computer science or mathematics. Familiarity with programming languages like Python or R, experience with big data tools (e.g., TensorFlow, SQL, Hadoop), and possibly certifications in data science platforms are typically required. Excellent problem-solving, communication, and collaboration skills help you translate data insights into impactful business solutions. These skills ensure you can extract meaningful insights from complex data and drive innovation in a fast-paced, data-driven environment.

What does a Data Scientist at Google do?

A Data Scientist at Google is responsible for analyzing large and complex data sets to help inform business decisions, develop new products, and improve user experiences. They use statistical analysis, machine learning, and data visualization techniques to uncover insights from data. Data Scientists at Google often collaborate with engineers, product managers, and other stakeholders to solve challenging problems and drive innovation across various products and services.

What is the difference between Data Scientist Google vs Data Analyst Google?

AspectData Scientist GoogleData Analyst Google
Required CredentialsBachelor's/Master's in CS, Statistics, or related; often a PhD for advanced rolesBachelor's in related fields; certifications like Google Data Analytics are common
Work EnvironmentDeveloping models, advanced analytics, machine learning projectsData cleaning, reporting, visualization, basic analysis
Employer & Industry UsageTech giants, startups, industries leveraging AI and MLBusiness intelligence, marketing, finance across various sectors

Data Scientist Google focuses on building predictive models and advanced analytics, requiring higher technical skills and often advanced degrees. Data Analyst Google handles data interpretation, reporting, and visualization, with a focus on business insights. Both roles are essential but differ in complexity and scope.

More about Data Scientist Google jobs
What cities are hiring for Data Scientist Google jobs? Cities with the most Data Scientist Google job openings:
What states have the most Data Scientist Google jobs? States with the most job openings for Data Scientist Google jobs include:
Infographic showing various Data Scientist Google job openings in the United States as of June 2026, with employment types broken down into 50% Full Time, 25% Part Time, and 25% Contract. Highlights an 90% Physical, 3% Hybrid, and 7% Remote job distribution, with an average salary of $122,738 per year, or $59 per hour.

Senior Data Scientist

bet365

Denver, CO

Full-time

Posted 27 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

As a Senior Data Scientist, you will accelerate our end-to-end machine learning lifecycle, building on our strong data science foundation to scale impact and automate business decisions.

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 leadership role where you will champion rapid iteration and innovation, this will be instrumental in elevating our ability to deliver measurable value. You will be responsible for the end-to-end lifecycle of machine learning solutions that optimize our Sports and Gaming products, from development to automated deployment and monitoring.

This is an exciting opportunity to apply cutting-edge data science and MLOps principles in a fast-paced, high-impact environment, tackling complex challenges in areas like Trading, Fraud, Responsible Gaming, and Personalization.

The listed salary for this position is $135,000 – $150,000 annually.

Qualifications
  • PhD or MSc in a quantitative field such as Computer Science, Statistics, or Engineering, or equivalent industry experience delivering complex data science projects.
  • Demonstrable experience deploying and maintaining machine learning systems in a production environment with measurable business impact.
  • Strong programming skills in Python and deep expertise in data science libraries such as, Scikit-learn, Pandas, NumPy, XGBoost.
  • Advanced proficiency in SQL, with hands-on experience querying and manipulating large, complex datasets, preferably with Google BigQuery.
  • Extensive hands-on experience with Google Cloud Platform (GCP), including building and automating ML workflows with Vertex AI pipelines, managing datasets, training models, and deploying to Vertex AI.
  • Experience using collaborative development environments such as Vertex AI Workbench for rapid prototyping, exploration, and analysis.
  • Experience leveraging other core GCP services such as BigQuery, Cloud Storage, and Cloud Functions to build end-to-end data solutions.
  • Solid understanding of CI/CD principles and tools such as Cloud Build or GitLab CIfor automating ML workflows.
  • Experience with containerization such as Docker, Kubernetes/GKE.

Additional Information
  • Owning the full data science lifecycle, from initial ideation and rapid prototyping in tools such as Vertex AI Workbench, to deploying production-grade models and pipelines that are robust, scalable, and automated.
  • Leading the implementation of advanced MLOps principles within our Google Cloud environment, designing, building, and maintaining CI/CD/CT pipelines for automated model deployment using Vertex AI Pipelines and other GCP services.
  • Partnering proactively with stakeholders in Product, Responsible Gaming, Trading, and other teams to identify high impact opportunities and translate complex business needs into tangible data science use cases.
  • Building and implementing frameworks for automated model testing, validation, and monitoring using tools such as Vertex AI Model Monitoring to detect drift and ensure performance at scale.
  • Designing, implementing, and rigorously analyzing A/B tests and other experiments to measure the impact of models and strategies, ensuring data-driven solutions deliver clear, quantifiable value.
  • Researching and championing the adoption of innovative data science and MLOps techniques, tools, and methodologies that solve problems efficiently, prioritizing impact over complexity.
  • Acting as a technical leader and mentor for other data scientists, fostering a culture of continuous learning and high-velocity execution.

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.