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Hourly Google Data Science Jobs in Raleigh, NC (NOW HIRING)

Lead Forward Deployed Engineer - AWS

Raleigh, NC · On-site

$99K - $131K/yr

Bachelor's degree (or equivalent) in Computer Science, Data Science or Engineering * 7+ years of ... Experience with cloud environments (AWS, Azure, and/or Google Cloud) and common platform services ...

Lead Forward Deployed Engineer, Palantir

Raleigh, NC · On-site

$99K - $131K/yr

Bachelor's degree (or equivalent) in Computer Science, Data Science or Engineering * 7+ years of ... Experience with cloud environments (AWS, Azure, and/or Google Cloud) and common platform services ...

Lead Forward Deployed Engineer, Snowflake

Raleigh, NC · On-site

$99K - $131K/yr

Bachelor's degree (or equivalent) in Computer Science, Data Science or Engineering. * 7+ years of ... Experience with cloud environments (AWS, Azure, and/or Google Cloud) and common platform services ...

Bachelor's degree (or equivalent) in Computer Science, Data Science or Engineering * 3+ years of ... Experience with cloud environments (AWS, Azure, and/or Google Cloud) and common platform services ...

Senior Forward Deployed Engineer- AWS

Raleigh, NC · On-site

$101K - $139K/yr

Required qualifications Bachelor's degree (or equivalent) in Computer Science, Data Science or ... or Google Cloud) and common platform services (storage, compute, IAM, networking) Demonstrated ...

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Hourly Google Data Science information

See Raleigh, NC salary details

$36.5K

$119.3K

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How much do hourly google data science jobs pay per year?

As of Jul 16, 2026, the average yearly pay for hourly google data science in Raleigh, NC is $119,312.00, according to ZipRecruiter salary data. Most workers in this role earn between $95,800.00 and $132,200.00 per year, depending on experience, location, and employer.

What is the hourly rate for a data scientist?

The hourly rate for a data scientist varies based on experience, location, and industry, but typically ranges from $30 to $100 per hour. Entry-level data scientists may earn closer to the lower end, while experienced professionals with specialized skills in machine learning and data analysis tools can command higher rates.

What are the typical daily responsibilities of an Hourly Google Data Science role?

As an Hourly Google Data Science professional, you can expect to work on data cleaning, exploratory data analysis, and supporting ongoing projects with statistical insights. Your day may involve collaborating with product managers and engineers to define metrics, analyze user behavior, and present findings through clear visualizations. Because the role is hourly, tasks are often project-based with a strong emphasis on timely deliverables and adapting to shifting priorities. Collaboration tools and regular check-ins help ensure alignment with the team and project goals.

Is 40 too late for data science?

Age is not a barrier to becoming a data scientist; many professionals transition into data science later in their careers. Success depends on acquiring relevant skills such as programming, statistics, and machine learning, often through online courses or certifications, regardless of age.

What is the 80 20 rule in data science?

In data science, the 80/20 rule, also known as Pareto principle, suggests that roughly 80% of results come from 20% of the efforts or data. Data scientists often focus on the most impactful features or data subsets to optimize model performance and efficiency.

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

To thrive as an Hourly Google Data Scientist, you generally need strong analytical skills, a background in statistics or computer science, and experience with data modeling and analysis. Familiarity with programming languages like Python or R, as well as tools such as SQL, TensorFlow, and Google Cloud Platform, is typically required. Exceptional problem-solving abilities, communication skills, and a collaborative mindset help individuals stand out in this role. These skills are crucial for extracting actionable insights from data, effectively presenting findings, and driving impactful decisions within Google's fast-paced environment.

How much does Google pay a data scientist?

Google data scientists typically earn an average salary ranging from $120,000 to $170,000 per year, depending on experience, location, and level. Compensation may also include bonuses, stock options, and benefits, with roles often requiring proficiency in machine learning, programming, and data analysis tools.

What is an Hourly Google Data Science job?

An Hourly Google Data Science job refers to a data science role at Google where an individual is compensated based on the number of hours worked, rather than receiving a fixed annual salary. These positions may be contract-based, freelance, or part of a temporary staffing arrangement. Hourly data scientists at Google typically analyze large datasets, build predictive models, and help inform business decisions using statistical and machine learning techniques. This role requires strong analytical skills, programming expertise, and familiarity with tools such as Python, R, and SQL. It can be a good option for those seeking flexible work arrangements or project-based employment.
What are popular job titles related to Hourly Google Data Science jobs in Raleigh, NC? For Hourly Google Data Science jobs in Raleigh, NC, the most frequently searched job titles are:
What job categories do people searching Hourly Google Data Science jobs in Raleigh, NC look for? The top searched job categories for Hourly Google Data Science jobs in Raleigh, NC are:
What cities near Raleigh, NC are hiring for Hourly Google Data Science jobs? Cities near Raleigh, NC with the most Hourly Google Data Science job openings:
Senior Machine Learning Engineer III

Senior Machine Learning Engineer III

LexisNexis

Raleigh, NC • Hybrid

$118K - $219K/yr

Full-time

Posted 15 days ago


LexisNexis rating

7.6

Company rating: 7.6 out of 10

Based on 17 frontline employees who took The Breakroom Quiz

162nd of 451 rated business services


Job description

hackajob is collaborating with LexisNexis to connect them with exceptional professionals for this role.

Are you looking to develop your Machine Learning Engineer career?

Do you enjoy coaching others to achieve high standards?

This is a full-time position based in Raleigh, NC.

(Hybrid - 3 days in office)

About the Role

We are seeking a Consultant-level Machine Learning Engineer to lead the implementation and scaling of AI systems for legal products. This role focuses on how to build and scale—owning system architecture, infrastructure, and productionization of ML/LLM solutions.

You will partner with Data Scientists to turn validated models and prototypes into reliable, high-performance, customer-facing systems.

Key Responsibilities

  • Architect and implement scalable ML/LLM systems in production.
  • Build and deploy LLM applications, including RAG pipelines and agentic systems.
  • Implement hybrid search systems (semantic + lexical) using embeddings and search platforms.
  • Develop and maintain APIs, microservices, and model serving infrastructure.
  • Build data pipelines and streaming systems for large-scale data processing.
  • Define and develop reusable frameworks, libraries, and infrastructure for AI/ML across teams.
  • Optimize systems for latency, scalability, reliability, and cost efficiency.
  • Establish best practices for deployment, monitoring, observability, and CI/CD.
  • Collaborate with Data Scientists to productionize models and integrate into products.
  • Provide technical leadership in system design and engineering standards.

Required Qualifications

  • Bachelor’s degree in Computer Science, Engineering, or a related field.
  • Strong experience implementing and scaling production ML/LLM systems.
  • Deep experience with LLM application development, including RAG and prompt orchestration.
  • Strong experience designing and implementing agentic systems using agent frameworks (e.g., LangChain, LangGraph, AutoGen, Google ADK), including orchestration of multi-step workflows in production environments.
  • Strong experience with hybrid search (semantic + lexical), embeddings, and search platforms (e.g., Solr, OpenSearch).
  • Expertise in distributed systems and cloud-native development, including AWS (S3, DynamoDB).
  • Experience with streaming and messaging systems (e.g., Kafka, SQS) and caching (e.g., Redis).
  • Proficiency in Python and experience with systems languages (e.g., Rust, Go, Scala).
  • Experience building scalable APIs (REST/GraphQL).
  • Experience with containerization and orchestration (Docker, Kubernetes).
  • Strong software engineering fundamentals (system design, testing, CI/CD).

Preferred Qualifications

  • Experience with LLM platforms (e.g., ChatGPT/OpenAI, Claude, Gemini, LangChain, Google ADK).
  • Experience with DevOps and infrastructure as code (e.g., Terraform, CloudFormation, Jenkins).
  • Experience with big data technologies (e.g., Spark, Hadoop).
  • Familiarity with graph databases (e.g., Dgraph, Neo4j, Neptune).
  • Experience building high-availability, low-latency systems.
  • Experience in legal or regulatory domains.

Key Competencies

  • Strong system architecture and scalability mindset.
  • Ownership of implementation, performance, and reliability.
  • Ability to translate data science solutions into production systems.
  • Cross-functional collaboration with DS, product, and platform teams.
  • Excellent debugging, optimization, and operational skills.
  • Clear communication of technical designs and trade-offs.

#AIFluent

U.S. National Base Pay Range: $118,300 - $219,800. Geographic differentials may apply in some locations to better reflect local market rates.

This job is eligible for an annual incentive bonus.

We know your well-being and happiness are key to a long and successful career. We are delighted to offer country specific benefits. Click here to access benefits specific to your location.

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