Data Scientist Jobs
Data Scientist jobs are open from entry-level to staff and principal across technology, healthcare, finance, and retail, with specializations in machine learning engineering, natural language processing, and applied analytics. Scan the live roles below and apply to whichever ones fit.
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Showing 5 of 2,176+ Data Scientist jobs
INTRODUCTION
Cullerton Group has a new opportunity for a Data Scientist III. The work will be performed onsite in Morton, Illinois, or Dallas, Texas. This is a six-month position that can lead to permanent employment with our client. Compensation is $81/hr + full benefits (vision, dental, health insurance, 401k, and holiday pay).
JOB SUMMARY
The Data Scientist III will design and build enterprise AI agents that identify supply-chain disruptions, generate alerts, and automate corrective workflows. This position will use Dataiku, Snowflake Cortex, Python, and modern agentic AI frameworks to develop secure, scalable solutions based primarily on structured enterprise data. The engineer will focus on agent architecture, orchestration, integrations, testing, evaluation, governance, and production deployment. This role will also establish reusable best practices and help other team members develop expertise in Dataiku’s agentic AI capabilities.
KEY RESPONSIBILITIES
- Design and build AI agents using Dataiku and Snowflake Cortex
- Develop automated workflows using Dataiku recipes and Python
- Create multi-agent architectures supporting collaboration, planning, delegation, and workflow orchestration
- Integrate AI agents with Microsoft Teams, SharePoint, email, PDFs, APIs, and enterprise data sources
- Implement role-based access controls, authorization models, guardrails, auditability, and governance standards
- Develop offline and online evaluation methods for groundedness, relevance, hallucination detection, and task success
- Create automated regression tests, monitoring, observability, and performance-tracking capabilities
- Design human-in-the-loop approval processes, escalation paths, and feedback mechanisms
- Develop production-ready Dataiku WebApps and user experiences
- Optimize model selection, latency, token consumption, performance, and operating costs
- Test agent outputs, refine code, and communicate progress during daily stand-up meetings
- Establish reusable agent frameworks, reference architectures, prompts, tools, and development standards
- Share technical knowledge and train team members on agentic AI technologies and practices
BASIC QUALIFICATIONS
- Bachelor’s degree in artificial intelligence, data science, computer science, or a related quantitative or technical field
- 5–7 years of relevant data science, artificial intelligence, machine learning, or software development experience
- Demonstrated experience building AI agents with Dataiku and Snowflake Cortex using structured data
- Strong Python programming experience, including developing workflow automation and programming logic
- Experience using Dataiku recipes for enterprise workflow automation
- Experience with LangGraph, LangChain, CrewAI, or comparable agentic AI frameworks
- Knowledge of multi-agent architecture, collaboration, planning, delegation, and orchestration patterns
- Experience creating reusable agent frameworks and reference architectures
- Understanding of RBAC, authorization, guardrails, security, governance, auditability, and compliance
- Experience integrating AI solutions with APIs and enterprise collaboration and data platforms
- Knowledge of event-driven and batch-processing architectures
- Experience evaluating, testing, monitoring, and operationalizing AI agents
- Understanding of prompt engineering, agent design patterns, human-in-the-loop workflows, and escalation processes
- Ability to work onsite in Morton, Illinois, or Dallas, Texas
- Strong teamwork, communication, teaching, and knowledge-sharing skills
PREFERRED QUALIFICATIONS
- Master’s or doctoral degree in a quantitative or technical discipline
- Experience with Model Context Protocol in multi-agent systems and agent-to-agent communication
- Experience developing Dataiku WebApps and production-ready user interfaces
- Knowledge of cloud platforms such as AWS, Microsoft Azure, or Google Cloud
- Experience with advanced statistical methods, machine learning, and data visualization
- Familiarity with industrial equipment, product analytics, aftermarket analytics, demand forecasting, or supply-chain analytics
- Experience mentoring or upskilling technical teams in emerging AI technologies
- Experience optimizing LLM selection, deployment, latency, performance, token use, and operational costs
WHY THIS ROLE?
This position offers an opportunity to apply emerging agentic AI technology to meaningful supply-chain challenges with direct operational impact. The successful candidate will help shape enterprise standards for agent architecture, security, evaluation, integration, and deployment while working on a focused project team. The role also provides an opportunity to serve as a technical expert and expand the organization’s capabilities through hands-on development and knowledge sharing. Cullerton Group provides a professional environment with growth potential and exposure to advanced enterprise AI initiatives.
INTRODUCTION
Cullerton Group has a new opportunity for a Data Scientist III. The work will be performed onsite in Morton, Illinois, or Dallas, Texas. This is a six-month position that can lead to permanent employment with our client. Compensation is $81/hr + full benefits (vision, dental, health insurance, 401k, and holiday pay).
JOB SUMMARY
The Data Scientist III will design and build enterprise AI agents that identify supply-chain disruptions, generate alerts, and automate corrective workflows. This position will use Dataiku, Snowflake Cortex, Python, and modern agentic AI frameworks to develop secure, scalable solutions based primarily on structured enterprise data. The engineer will focus on agent architecture, orchestration, integrations, testing, evaluation, governance, and production deployment. This role will also establish reusable best practices and help other team members develop expertise in Dataiku’s agentic AI capabilities.
KEY RESPONSIBILITIES
- Design and build AI agents using Dataiku and Snowflake Cortex
- Develop automated workflows using Dataiku recipes and Python
- Create multi-agent architectures supporting collaboration, planning, delegation, and workflow orchestration
- Integrate AI agents with Microsoft Teams, SharePoint, email, PDFs, APIs, and enterprise data sources
- Implement role-based access controls, authorization models, guardrails, auditability, and governance standards
- Develop offline and online evaluation methods for groundedness, relevance, hallucination detection, and task success
- Create automated regression tests, monitoring, observability, and performance-tracking capabilities
- Design human-in-the-loop approval processes, escalation paths, and feedback mechanisms
- Develop production-ready Dataiku WebApps and user experiences
- Optimize model selection, latency, token consumption, performance, and operating costs
- Test agent outputs, refine code, and communicate progress during daily stand-up meetings
- Establish reusable agent frameworks, reference architectures, prompts, tools, and development standards
- Share technical knowledge and train team members on agentic AI technologies and practices
BASIC QUALIFICATIONS
- Bachelor’s degree in artificial intelligence, data science, computer science, or a related quantitative or technical field
- 5–7 years of relevant data science, artificial intelligence, machine learning, or software development experience
- Demonstrated experience building AI agents with Dataiku and Snowflake Cortex using structured data
- Strong Python programming experience, including developing workflow automation and programming logic
- Experience using Dataiku recipes for enterprise workflow automation
- Experience with LangGraph, LangChain, CrewAI, or comparable agentic AI frameworks
- Knowledge of multi-agent architecture, collaboration, planning, delegation, and orchestration patterns
- Experience creating reusable agent frameworks and reference architectures
- Understanding of RBAC, authorization, guardrails, security, governance, auditability, and compliance
- Experience integrating AI solutions with APIs and enterprise collaboration and data platforms
- Knowledge of event-driven and batch-processing architectures
- Experience evaluating, testing, monitoring, and operationalizing AI agents
- Understanding of prompt engineering, agent design patterns, human-in-the-loop workflows, and escalation processes
- Ability to work onsite in Morton, Illinois, or Dallas, Texas
- Strong teamwork, communication, teaching, and knowledge-sharing skills
PREFERRED QUALIFICATIONS
- Master’s or doctoral degree in a quantitative or technical discipline
- Experience with Model Context Protocol in multi-agent systems and agent-to-agent communication
- Experience developing Dataiku WebApps and production-ready user interfaces
- Knowledge of cloud platforms such as AWS, Microsoft Azure, or Google Cloud
- Experience with advanced statistical methods, machine learning, and data visualization
- Familiarity with industrial equipment, product analytics, aftermarket analytics, demand forecasting, or supply-chain analytics
- Experience mentoring or upskilling technical teams in emerging AI technologies
- Experience optimizing LLM selection, deployment, latency, performance, token use, and operational costs
WHY THIS ROLE?
This position offers an opportunity to apply emerging agentic AI technology to meaningful supply-chain challenges with direct operational impact. The successful candidate will help shape enterprise standards for agent architecture, security, evaluation, integration, and deployment while working on a focused project team. The role also provides an opportunity to serve as a technical expert and expand the organization’s capabilities through hands-on development and knowledge sharing. Cullerton Group provides a professional environment with growth potential and exposure to advanced enterprise AI initiatives.
Data Scientist Jobs by Experience Level
Top Cities Hiring Data Scientists
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Find Data Scientist JobsData Scientist Job Market
Who's Hiring
- Booz Allen Hamilton91
- Google72
- Intuit46
- Amazon46
- CVS Health39
Top Industries Hiring
- Technology & Software85
- Electronics & Hardware15
- Staffing & Recruiting13
- Banking & Financial Services13
- Consulting & Professional Services13
What Employers Look For
The qualifications that appear most often in data scientist jobs.
- Proficiency in Python and SQL for data manipulation and analysis
- Experience building and deploying machine learning models in production
- Familiarity with cloud platforms such as AWS, Azure, or Google Cloud
- Bachelor's or master's degree in statistics, computer science, or a related quantitative field
- Ability to communicate findings and model results clearly to non-technical stakeholders
- Experience with data visualization tools such as Tableau, Power BI, or Looker
Tips for Your Data Scientist Job Search
Tailor your resume to each posting
Copy the exact model names and tools listed in the job description, such as XGBoost, PyTorch, or dbt, into your resume where you've used them. Applicant tracking systems score resumes on keyword matches before a human ever reads them.
Show model impact, not just methods
Hiring managers want to know what your model did in production, not just that you built one. Replace phrases like 'developed a classification model' with outcomes: how it changed a decision, reduced error, or moved a business metric.
Build a portfolio that reflects the industry
A healthcare data scientist role and a fintech one call for different demos. Pick one or two portfolio projects that use data problems from your target industry, even if the work was done independently, so reviewers immediately see relevant context.
Apply early to roles that fit
Migrate Mate lists data scientist openings from across the United States in one place, so you can find roles that match and apply directly to each listing.
Prepare for a take-home case study
Most data scientist interviews include a take-home assignment involving messy real-world data. Practice writing clean, commented code and a short executive summary alongside your analysis, since both are evaluated separately in most scoring rubrics.
Negotiate by anchoring to scope, not title
When discussing offers, frame your ask around the complexity of the modeling work, the expected data volume, and cross-functional scope rather than just job title. That framing shifts the conversation toward business value and tends to support a stronger outcome.
Data Scientist Jobs: Frequently Asked Questions
Which companies are hiring the most data scientists?
Booz Allen Hamilton, Google, and Intuit are hiring the most data scientists right now, with openings concentrated in California, Virginia, and Texas, based on current listings on Migrate Mate as of September 2026. Volume and location shift month to month, so checking current listings gives you the most accurate picture.
How many data scientist jobs are remote?
About 68% of data scientist openings are fully remote or hybrid as of September 2026, making it one of the more remote-accessible roles in the technology sector. Machine learning research, analytics engineering, and NLP roles tend to have the highest share of fully remote postings compared to embedded or product-facing data science positions.
How do you become a data scientist?
Most data scientists start by building fluency in Python and SQL, then move into statistics, machine learning fundamentals, and a tool like scikit-learn or PyTorch. A degree in a quantitative field helps, but employers weigh portfolio projects and demonstrated modeling skills heavily. Working through real datasets, publishing notebooks, and completing a capstone project in your target industry will move your application forward faster than coursework alone.
How do you get hired as a data scientist with little experience?
Focus on one specialized area, such as natural language processing, computer vision, or time-series forecasting, rather than trying to show breadth. Build two or three end-to-end projects that go from raw data to a deployed or shareable model output. Entry-level and associate data scientist roles, as well as data analyst positions with modeling components, are realistic starting points and often lead to a full data scientist role within a year or two.
What does the data scientist interview process look like?
Most data scientist interview processes include a recruiter screen, a technical phone interview covering statistics and Python, a take-home assignment or case study, and a final loop with the team that often includes a presentation of your case study findings. Some companies add a system design or data modeling round. The full process typically runs across several weeks from first contact to offer.
Where can I find and apply to data scientist jobs?
You can find and apply to data scientist jobs on Migrate Mate, which lists current openings from employers across the United States. Search the listings to find roles that match your background and apply directly to each one that fits. New postings are added regularly, so checking back often gives you access to the most current opportunities.
See All 2,176+ Data Scientist Jobs
Find roles that match your experience and apply in just a few clicks.
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