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Google Data Science Jobs in Michigan (NOW HIRING)

FastTek

Data Architect Specialist

Dearborn, MI

$58.50 - $75.25/hr

Master's degree in Business, Data Science, Analytics, or a related field. * Experience with cloud platforms such as Amazon Web Services, Microsoft, or Google. * Familiarity with SQL, Python, data ...

NITS Solutions

Data and Security Manager

Novi, MI

Required Qualifications • Bachelor's degree in Computer Science, Information Security, Data ... or Google Cloud) and securing data pipelines • Familiarity with security frameworks and ...

FastTek

Data Engineer

Dearborn, MI · On-site

$105K - $126K/yr

Google Cloud Platform - Familiarity with advanced GCP services beyond core compute and storage ... Acting as a bridge between technical teams (Data Science, Security) and business stakeholders to ...

FastTek

Data Engineer

Dearborn, MI · On-site

$105K - $126K/yr

Google Cloud Platform - Familiarity with advanced GCP services beyond core compute and storage ... Acting as a bridge between technical teams (Data Science, Security) and business stakeholders to ...

Saanvi Technologies

Senior Data Product Manager

Dearborn, MI · On-site

$116K - $153K/yr

Master's degree in Business, Data Science, Analytics, or a related field. * Experience with cloud platforms such as Amazon Web Services, Microsoft, or Google. * Familiarity with SQL, Python, data ...

Ford Motor Company

Senior Data Engineer

Redford, MI · On-site

$85K - $192K/yr

Master's degree in Data Science, Computer Science, Statistics, Engineering, or a related ... Experience working within Google Cloud Platform (GCP) (Vertex AI, BigQuery, Dataflow). * Domain ...

Stellantis

Data Engineer

Auburn Hills, MI · On-site

$108K - $130K/yr

You will work at the intersection of software engineering and data science, ensuring that our data ... Comprehensive experience working with Big Data platforms (i.e., Spark, Google Big Query, Azure, AWS ...

Pwc

AI & GenAI Data Scientist - Manager

Detroit, MI · On-site

$99K - $232K/yr

... Science, Artificial Intelligence and Robotics - At least one of the following: Certifications aligned to data engineering, machine learning, and cloud platforms, including AWS, Google Cloud ...

Pwc

AI & GenAI Data Scientist - Manager

Grand Rapids, MI · On-site

$99K - $232K/yr

... Science, Artificial Intelligence and Robotics - At least one of the following: Certifications aligned to data engineering, machine learning, and cloud platforms, including AWS, Google Cloud ...

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$21.5K

$101.8K

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How much do google data science jobs pay per year?

As of Jun 11, 2026, the average yearly pay for google data science in Michigan is $101,809.00, according to ZipRecruiter salary data. Most workers in this role earn between $64,984.00 and $127,774.00 per year, depending on experience, location, and employer.

Can data scientists make $300k?

Data scientists, including those working at Google, can earn $300,000 or more annually, especially with senior roles, extensive experience, advanced skills in machine learning and big data tools, and in high-cost-of-living areas. Compensation often includes base salary, bonuses, and stock options, which contribute to total earnings at this level.

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 tools being highly valued.

Is 40 too late for data science?

Age is not a barrier to becoming a data scientist, including at age 40. Success in data science depends on skills, experience, and continuous learning of tools like Python, R, and SQL, rather than age. Many professionals transition into data science later in their careers and find opportunities with relevant certifications and a strong portfolio.

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 is the average salary for a Data Scientist at Google?

The average salary for a Data Scientist at Google is approximately $120,000 to $150,000 per year, depending on experience, location, and level. Senior roles or those with specialized skills in machine learning and data analysis can earn higher compensation, often including bonuses and stock options.
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

Machine Learning Engineer (09235)

Talent Management Plus, Inc.

Detroit, MI

$113K - $136K/yr

Other

Posted 16 days ago

Job description

Position: Machine Learning Engineer (09235)
Location: Detroit, MI
Duration: 6 months+
Summary:
The Data Science and Analytics Center of Excellence (COE) is responsible for leading the creation and development of the overall strategy and direction of data science and advanced analytics - including ensuring continuity and seamless extension of existing programs, the development of a short- and long-term vision and roadmap, and defining and institutionalizing the role that data and analytics play throughout the organization as the fuel that drives and shapes client's priorities and serves as an accelerant for client's progress.
Description:
The ML Engineer is a key player in the Integrated Tech Programs & Strategies team. This role will be responsible for data engineering, data science Model deployment, testing and management for the end-to-end ML and data pipeline including data products. This role will leverage Client's AI labs environment to enable the delivery in a common data lake and products.
Responsibilities:
  • Responsible for building and managing end-to-end data pipelines and operations from ingestion and integration through delivery for the data science prototypes and data products.
  • Adept at queries, report writing and presenting findings, analyze large complex datasets to extract insights and decide on the appropriate technique.
  • Understand and use data and ML fundamentals, including data structures, algorithms, computability and complexity and computer architecture.
  • Collaborate with data engineers to build data and model pipelines, manage the infrastructure and data pipelines needed to bring code to production.
  • Provide support to engineers and product managers in implementing machine learning in the product.
  • Drive the design, building and launching of new data models and ML/Data pipelines in production.
  • Identify, analyze, and interpret trends or patterns in complex data sets.
  • Consulting with managers, Product owners to determine and refine machine learning objectives.
  • Transforming data science prototypes and applying appropriate ML tools and technologies.
  • Contribute and support the development of the overall data science and machine learning strategy and roadmap.

Required Skills:
  • Bachelor's degree in computer science, or equivalent IT knowledge/experience.
  • 2+ years of relevant work experience in Data Analysis, Data Engineer, Data Science & Data Integration.
  • Must have strong data infrastructure, data engineering and Machine Learning skills
  • Must have a proven track record of leading and scaling data pipelines, ML Model deployments in a cloud/on prem/big data environment
  • Strong knowledge of and experience with reporting packages (Business Objects etc.), databases (SQL etc.), programming (XML, JavaScript, or ETL frameworks).
  • Programming languages: SQL, Spark, Python, R, Jupyter Notebooks, Java, Scala, C++
  • Data Exploration and ETL: Alteryx, Talend, H2O, Informatica, Data Stage, Azure Data explorer, Azure Data Factory.
  • Data Warehouse Solutions: Redshift, Snowflake, Postgres, Data Lake.
  • Big Data technologies: Azure, AWS, Hadoop, Spark, Hive, Kafka, Flume, NoSQL stores (HBase, Cassandra, DynamoDB, MongoDB).
  • Cloud storage: S3, GCS, ADLS, Blob.
  • Machine Learning: Cloudera Data Science Workbench, Azure ML, Amazon ML, Google AutoML, Vertex AI.
  • Data Visualization Solutions: MS Power BI, Looker, Tableau, Azure Streaming Analytics, Data Lake Analytics, Azure Time Series Insights, Azure Synapse Analytics.
  • CI/CD and Code Management: Git, Maven, Docker, Jenkins, Azure Dev Ops.
  • Experience working with Data engineering, Data science, ETL teams and managing implementing projects that utilize big data, advanced analytics, and machine learning technologies.
  • Hands-on experience in building data and ML pipelines from variety of sources such as data warehouses and in-memory OLAP models, as well as experience in NoSQL/cloud.
  • Strong understanding of data, ML Models, Big Data, Relational databases, streaming and batch data processing.
  • Knowledge of machine learning evaluation metrics and best practice.
  • Strong experience building end-to-end data view with focus on integration.

Preferred Skills:
  • Experience working with on-prem and cloud-based data warehouses
  • Experience with cloud-based personalization and machine-learning applications.
  • Experience working for consumer or business-facing digital brands.

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