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Google Data Science Jobs in Tennessee (NOW HIRING)

Principal Data Scientist

Shelbyville, TN ยท On-site

$140 - $180/hr

Google Cloud Professional Machine Learning Engineer, Professional Data Engineer, or relevant Google Cloud AI certifications. * Data Science / ML: Databricks Machine Learning, TensorFlow, or other ...

Data Scientist

Nashville, TN ยท On-site

$100 - $130/hr

We are seeking a highly skilled Senior Data Scientist with strong experience in cloud-based data platforms (Google Cloud or similar), Python/PySpark development, and advanced timeโ€‘series ...

Work with data engineers, data architects, data scientists, and other internal stakeholders to ... Deploy and support cloud-native data pipelines in Google Cloud Platform (GCP), including BigQuery ...

Work with data engineers, data architects, data scientists, and other internal stakeholders to ... Deploy and support cloud-native data pipelines in Google Cloud Platform (GCP), including BigQuery ...

Work with data engineers, data architects, data scientists, and other internal stakeholders to ... Deploy and support cloud-native data pipelines in Google Cloud Platform (GCP), including BigQuery ...

Work with data engineers, data architects, data scientists, and other internal stakeholders to ... Deploy and support cloud-native data pipelines in Google Cloud Platform (GCP), including BigQuery ...

... 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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Google Data Science information

See Tennessee salary details

$24.7K

$117K

$202.4K

How much do google data science jobs pay per year?

As of Aug 27, 2026, the average yearly pay for google data science in Tennessee is $117,017.00, according to ZipRecruiter salary data. Most workers in this role earn between $74,692.00 and $146,860.00 per year, depending on experience, location, and employer.

What is a Google data science?

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 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.

What are the most commonly searched types of Google Data Science jobs in Tennessee?

The most popular types of Google Data Science jobs in Tennessee are:

What are popular job titles related to Google Data Science jobs in Tennessee?

For Google Data Science jobs in Tennessee, the most frequently searched job titles are:

What cities in Tennessee are hiring for Google Data Science jobs?

Cities in Tennessee with the most Google Data Science job openings:

Infographic showing various Google Data Science job openings in Tennessee as of August 2026, with employment types broken down into 1% As Needed, 83% Full Time, 12% Part Time, and 4% Contract. Highlights an 83% Physical, 5% Hybrid, and 12% Remote job distribution, with an average salary of $117,017 per year, or $56.3 per hour.

Principal Data Scientist

Shelbyville, TN โ€ข On-site

$140 - $180/hr

Other

Posted 15 days ago


Job description

Requisition Number: 105937

Principal Data Scientist

Focus: Clinical / HLS, Google Cloud Gen AI, Agents, and Applied ML

Location: Nashville, TN area preferred

Insight at a Glance
  • 14,000+ engaged teammates globally
  • $8.2 billion in revenue in 2025
  • Certified as a Great Place to work in 9 Countries in 2025
  • Fortune 500 Company (No. 447) in 2025
  • Received 25+ industry and partner awards in the past year
  • $1.4M+ total charitable contributions in 2024 by Insight globally
About the Role

Now is the time to bring your expertise to Insight. Healthcare and life sciences organizations are moving quickly to adopt generative AI, machine learning, and agentic systems, but many still face a critical challenge: converting complex clinical data and operational workflows into safe, measurable, production-ready AI solutions.

We are seeking a Principal Data Scientist with deep experience in clinical or healthcare and life sciences environments, Google Cloud generative AI, agentic AI patterns, and applied machine learning. In this client-facing consulting role, you will help healthcare organizations design, validate, and operationalize AI solutions that improve decision support, streamline workflows, and unlock value from structured and unstructured clinical data.

You will bridge the gap between clinical stakeholders, technical engineering teams, and executive leadership, ensuring that AI solutions are not only innovative, but also responsible, explainable, secure, and aligned to healthcare business outcomes.

What You'll Do
  • Clinical AI Solution Design: Lead the design of AI and ML solutions for healthcare and life sciences use cases, including clinical decision support, workflow automation, operational intelligence, patient-facing insights, and knowledge retrieval across complex healthcare data environments.
  • Google Cloud Gen AI Architecture: Design and guide implementation of generative AI solutions using the Google Cloud AI ecosystem, including Vertex AI, Gemini, model evaluation workflows, retrieval-augmented generation patterns, and enterprise-grade deployment approaches.
  • Agentic Systems for Healthcare Workflows: Architect and prototype agentic AI solutions that can reason across clinical, operational, and knowledge-based workflows while maintaining appropriate controls, traceability, and human-in-the-loop oversight.
  • Applied Machine Learning: Develop and guide machine learning approaches for classification, prediction, summarization, entity extraction, document intelligence, and other healthcare-relevant use cases using structured, semi-structured, and unstructured data.
  • Data Readiness and Clinical Context: Partner with client stakeholders to evaluate data quality, lineage, terminology, interoperability considerations, and clinical workflow fit before advancing AI use cases into production.
  • Model Evaluation and Responsible AI: Define evaluation strategies for accuracy, relevance, bias, safety, drift, explainability, and clinical appropriateness, ensuring AI outputs can be trusted by healthcare stakeholders.
  • Technical Advisory and Client Engagement: Serve as a senior technical advisor to client leaders, translating complex data science and Gen AI concepts into practical roadmaps, business value narratives, and implementation plans.
  • Thought Leadership and Delivery Enablement: Mentor data scientists, engineers, and consultants while contributing reusable healthcare AI patterns, accelerators, evaluation frameworks, and delivery playbooks for Insight.
What Weโ€™re Looking For
  • Experience: 10+ years of experience in data science, machine learning, healthcare analytics, clinical AI, or applied AI solution delivery, ideally within consulting or enterprise client environments.
  • Healthcare / HLS Domain Expertise: Strong understanding of clinical workflows, healthcare operations, clinical documentation, patient data, provider environments, payer/provider dynamics, or life sciences data use cases.
  • Google Cloud AI Expertise: Handsโ€‘on experience with Google Cloud AI and data services, especially VertexAI, Gemini, BigQuery, document AI, model deployment, and enterprise ML workflows.
  • Generative AI and Agentic AI: Practical experience designing Gen AI and agentic solutions, including prompt engineering, tool use, orchestration patterns, RAG architectures, guardrails, and human review workflows.
  • Machine Learning Depth: Strong foundation in supervised and unsupervised learning, NLP, model evaluation, feature engineering, experimentation, and production ML lifecycle practices.
  • Responsible AI Mindset: Understanding of healthcare data sensitivity, PHI protection, explainability, model risk, clinical validation, and governance expectations for AIโ€‘enabled healthcare solutions.
  • Consulting Mindset: Exceptional communication skills with the ability to translate clinical and technical complexity into businessโ€‘aligned recommendations for executives, clinical leaders, and technology teams.
Preferred Certifications
  • Google Cloud / AI: Google Cloud Professional Machine Learning Engineer, Professional Data Engineer, or relevant Google Cloud AI certifications.
  • Data Science / ML: Databricks Machine Learning, TensorFlow, or other relevant ML and analytics certifications.
  • Healthcare / Governance: Certifications or training related to healthcare data, HIPAA, clinical analytics, Responsible AI, or AI governance are a plus.
What You Can Expect

Weโ€™re legendary for taking care of you, your family and to help you engage with your local community.

But what really sets us apart are our core values of Hunger, Heart, and Harmony, which guide everything we do, from building relationships with teammates, partners, and clients to making a positive impact in our communities.

Join us today, your ambITious journey starts here.

Equal Opportunity Employer

Insight is an equal opportunity employer, and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability status, protected veteran status, sexual orientation or any other characteristic protected by law.

At Insight, we celebrate diversity of skills and experience so even if you donโ€™t feel like your skills are a perfect match - we still want to hear from you!

Insight is an equal opportunity employer, and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability status, protected veteran status, sexual orientation or any other characteristic protected by law.

The position described above provides a summary of some the job duties required and what it would be like to work at Insight. For a comprehensive list of physical demands and work environment for this position.

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