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Google Data Science Jobs in Michigan (NOW HIRING)

Tech Tammina LLC

Data Scientists Modeling

Dearborn, MI · On-site

... data science (e.g., Python, R). Skills Preferred: • Experience working with cloud computing platforms, particularly Google Cloud Platform (GCP). • Experience with specific machine learning ...

Ford Motor Company

Senior Data Scientist

Dearborn, MI · On-site

Familiar with LLM orchestration workflows like Crew.ai, Langraph, Google ADK for quick development ... Master's degree in quantitative fields, such as Data Science, Engineering, Operations Research ...

Ford Motor Company

Senior Data Scientist

Dearborn, MI · On-site

... via Google Cloud Platform to optimize the delivery of value. You will interact with business ... Master's degree in quantitative fields, such as Data Science, Engineering, Operations Research ...

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Google Data Science information

Can a Data Scientist work in Google?

Yes, Data Scientists can work at Google, where they analyze large datasets, develop machine learning models, and use tools like Python and TensorFlow. Google typically requires relevant experience, strong analytical skills, and a background in computer science or related fields for data science roles.

How much do data scientists make at Google?

Data scientists at Google typically earn a median salary ranging from $120,000 to $160,000 per year, depending on experience, location, and level. Total compensation often includes bonuses, stock options, and other benefits, reflecting the company's competitive pay structure for technical roles requiring skills in machine learning, programming, and data analysis.

What are the key skills and qualifications needed to thrive in the Google Data Science position, and why are they important?

To thrive as a Google Data Science professional, you need a strong foundation in statistical analysis, machine learning, and data manipulation, often supported by a degree in a quantitative field such as computer science, statistics, or mathematics. Proficiency in programming languages like Python or R, experience with large-scale data processing tools (such as SQL, TensorFlow, or BigQuery), and familiarity with cloud-based platforms are commonly required. Excellent problem-solving, communication, and collaboration skills help set candidates apart in effectively translating complex data insights to varied stakeholders. These capabilities are crucial for driving impactful, data-driven decisions within cross-functional teams at Google.

How much does Google pay a Data Scientist?

Google Data Scientists typically earn a base salary ranging from $120,000 to $180,000 annually, with total compensation often including bonuses and stock options that can increase overall earnings. Compensation varies based on experience, location, and skill level, with advanced skills in machine learning and data analysis highly valued.

Is 40 too late for data science?

Age is not a barrier to becoming a data scientist, and many professionals successfully transition into the field at age 40 or later. Success depends on acquiring relevant skills such as programming, statistics, and data analysis, often through online courses or certifications, and building a strong portfolio. Employers value experience and problem-solving ability, making it possible to start a data science career at any age with dedication.

What is a Google Data Science job?

A Google Data Science job involves analyzing large datasets to provide insights and drive data-informed decisions. Data scientists at Google apply statistical modeling, machine learning, and analytical techniques to solve complex problems in products like Search, Ads, YouTube, and Cloud. They work closely with engineers, product managers, and business teams to develop data-driven solutions. Strong coding skills in Python or SQL, experience with big data tools, and a solid foundation in statistics are essential for this role.

What types of projects do Google Data Science professionals typically work on?

Google Data Science professionals engage in a wide variety of impactful projects, such as optimizing algorithms for product recommendations, improving user experiences through data-driven insights, and developing predictive models to inform business strategies. They often work closely with product managers, engineers, and designers to translate complex data findings into actionable solutions. The work environment is highly collaborative and fast-paced, with opportunities to contribute to innovative initiatives across different Google products and services. This dynamic setting allows data scientists to continuously expand their skill sets and take on new challenges, fostering both personal and professional growth.

What are the most commonly searched types of Google Data Science jobs in Michigan? The most popular types of Google Data Science jobs in Michigan are:
What are popular job titles related to Google Data Science jobs in Michigan? For Google Data Science jobs in Michigan, the most frequently searched job titles are:
What job categories do people searching Google Data Science jobs in Michigan look for? The top searched job categories for Google Data Science jobs in Michigan are:
What cities in Michigan are hiring for Google Data Science jobs? Cities in Michigan with the most Google Data Science job openings:
Google Data Science jobs near you
Infographic showing various Google Data Science job openings in Michigan as of July 2026, with employment types broken down into 1% As Needed, 82% Full Time, 13% Part Time, 1% Temporary, and 3% Contract. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution.

Data Scientists Modeling

Tech Tammina LLC

Dearborn, MI • On-site

Contractor

Re-posted 12 days ago

Job description

Role: Data Scientists Modeling
Location: Dearborn, MI (Hybrid)
Duration: Long term
Rate: Market

What You'll Do: 
•    Acquire, clean, and process messy, real-world data from various sources to prepare it for analysis and modeling. 
•    Perform rigorous Exploratory Data Analysis (EDA) to understand data characteristics, identify patterns, uncover hidden insights, and formulate hypotheses. 
•    Translate complex business questions and challenges into well-defined data science problems and analytical tasks. 
•    Develop, train, and evaluate statistical and machine learning models to address specific business needs (e.g., prediction, classification, clustering, forecasting). 
•    Collaborate closely with engineering and product teams to deploy models into production environments, ensuring scalability, reliability, and performance monitoring.
•    Communicate findings and model results clearly and effectively to technical and non-technical stakeholders, translating complex data analysis results into actionable business recommendations and solutions.
•    Iterate on models and approaches based on performance feedback and evolving business requirements. 
•    Stay up to date with the latest advancements in data science, machine learning, and relevant technologies.
Skills Required:
•    Demonstrated ability to deal with and process data from real-world sources. 
•    Experience performing Exploratory Data Analysis (EDA). 
•    Experience with model development (statistical modeling, machine learning). 
•    Familiarity with the process of deploying models into production or working alongside teams that do. 
•    Proven ability to translate business questions into data-driven problems.
•    Ability to translate data analysis results and model insights into clear, business-oriented solutions. 
•    Proficiency in at least one major programming language used in data science (e.g., Python, R).
Skills Preferred:
•         Experience working with cloud computing platforms, particularly Google Cloud Platform (GCP).
•         Experience with specific machine learning frameworks (e.g., scikit-learn, TensorFlow, PyTorch).
Experience Required:
•         Experience with data manipulation and analysis libraries/tools (e.g., Pandas, SQL).
Experience Preferred:
•         Experience in Auto Industry