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Contractual Full Stack Data Scientist Jobs (NOW HIRING)

FULL-STACK DATA ENGINEER at MOTOR INFORMATION SYSTEMS MOTOR Information Systems, an operating group of Hearst, is actively seeking a Full-Stack Data Engineer. Ideally, a hands-on data engineer who ...

FULL-STACK DATA ENGINEER at MOTOR INFORMATION SYSTEMS MOTOR Information Systems, an operating group of Hearst, is actively seeking a Full-Stack Data Engineer. Ideally, a hands-on data engineer who ...

Full Stack Data Engineer

Dearborn, MI · On-site

$138K - $178K/yr

Full Stack Data Engineer - positions offered by Ford Motor Company (Dearborn, Michigan). Note, this ... Science or a related field and 5 years of progressive, post-baccalaureate experience in the job ...

We are seeking a talented and experienced Full Stack Data Engineer to join our team. The ideal ... Collaborate with cross-functional teams including data scientists, analysts, and business ...

As a full-stack data scientist, you will turn complex operational signals into insight-and translate that insight into lightweight products, prototypes, and tools that reshape service delivery at ...

Full Stack Data Engineer

Dearborn, MI · On-site +1

$99K - $166K/yr

As a Full Stack Data Engineer supporting the Connected Vehicle Data Team, you will play a key role ... You'll Have... * Bachelor's degree in Computer Science, Software Engineering, Data Science ...

... as a full-stack data scientist who develops, optimizes, and scales models for the production environment • You connect the how and why using your knowledge of data science theories and ...

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Contractual Full Stack Data Scientist information

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$46K

$165K

$243.5K

How much do contractual full stack data scientist jobs pay per year?

As of Jun 9, 2026, the average yearly pay for contractual full stack data scientist in the United States is $165,018.00, according to ZipRecruiter salary data. Most workers in this role earn between $133,500.00 and $170,000.00 per year, depending on experience, location, and employer.

What is the difference between Contractual Full Stack Data Scientist vs Contractual Data Engineer?

AspectContractual Full Stack Data ScientistContractual Data Engineer
CredentialsDegree in Data Science, Computer Science, or related field; certifications in data analysis or machine learningDegree in Computer Engineering, Software Engineering, or related; certifications in cloud platforms or data pipeline tools
Work EnvironmentCollaborates with data analysts, machine learning engineers, and business teams on modeling and insightsFocuses on building, maintaining, and optimizing data pipelines and infrastructure
Industry UsageUsed across industries for data analysis, predictive modeling, and business insightsPrimarily in tech, finance, and e-commerce for data infrastructure and ETL processes

The Contractual Full Stack Data Scientist combines data analysis, modeling, and software skills to deliver insights and solutions, while the Contractual Data Engineer specializes in building and maintaining data infrastructure. Both roles are essential in data-driven organizations but focus on different aspects of the data lifecycle.

What are some common challenges faced by contractual full stack data scientists, and how can they be addressed?

Contractual full stack data scientists often face challenges such as adapting quickly to new teams and business domains, managing time constraints, and ensuring seamless handover of work at project completion. Since these roles typically involve both backend and frontend tasks, balancing diverse technical responsibilities while aligning with client expectations can be demanding. To address these challenges, it’s helpful to establish clear communication channels, document work thoroughly, and set realistic deliverables early in the contract. Proactively engaging with stakeholders and being flexible with new tools or workflows also support successful project outcomes.

What are Contractual Full Stack Data Scientists?

Contractual Full Stack Data Scientists are professionals hired on a contract basis to manage the end-to-end data science workflow for an organization. They are skilled in both frontend and backend development, as well as data engineering, data analysis, and machine learning. Their responsibilities often include collecting, processing, and analyzing data, developing predictive models, and deploying solutions into production environments. Unlike permanent employees, they typically work on specific projects or for a set period, offering flexibility to both the employer and the professional.

What are the key skills and qualifications needed to thrive as a Contractual Full Stack Data Scientist, and why are they important?

To thrive as a Contractual Full Stack Data Scientist, you need strong expertise in statistics, machine learning, data analysis, and software engineering, typically supported by a relevant degree and a portfolio of completed projects. Familiarity with programming languages such as Python or R, cloud platforms like AWS or Azure, and tools such as TensorFlow, SQL, and version control systems is essential. Excellent problem-solving, communication, and time management skills help you adapt quickly to varied client needs and collaborate effectively with cross-functional teams. These skills ensure the ability to deliver end-to-end data solutions that drive business value within project deadlines.
More about Contractual Full Stack Data Scientist jobs
What cities are hiring for Contractual Full Stack Data Scientist jobs? Cities with the most Contractual Full Stack Data Scientist job openings:
What are the most commonly searched types of Full Stack Data Scientist jobs? The most popular types of Full Stack Data Scientist jobs are:
What states have the most Contractual Full Stack Data Scientist jobs? States with the most job openings for Contractual Full Stack Data Scientist jobs include:
Infographic showing various Contractual Full Stack Data Scientist job openings in the United States as of May 2026, with employment types broken down into 1% As Needed, 66% Full Time, and 33% Part Time. Highlights an 91% Physical, 3% Hybrid, and 6% Remote job distribution, with an average salary of $165,018 per year, or $79.3 per hour.
Full-Stack Data Engineer

Full-Stack Data Engineer

Hearst

Troy, MI • On-site

Full-time

Posted 23 days ago


Hearst rating

6.7

Company rating: 6.7 out of 10

Based on 24 frontline employees who took The Breakroom Quiz

49th of 65 rated media


Job description

FULL-STACK DATA ENGINEER at MOTOR INFORMATION SYSTEMS

MOTOR Information Systems, an operating group of Hearst, is actively seeking a Full-Stack Data Engineer. Ideally, a hands-on data engineer who possesses a strong passion for designing, optimizing, refactoring, and upgrading complex data solutions! MOTOR's primary product is Automotive Content, and we need someone who can help us support our Insights-based product suite.

We are looking for someone who wants to be part of our mission to transform the future. We have a rare opportunity for you to use your talent, passion, and expertise to help drive this massive change in how we build our user experience across our product lines, and how consumers experience the MOTOR Product Platform.

This position offers excellent career growth and promotional opportunities, stellar compensation, and the ability to work with the world's premier provider of aftermarket automotive data. Hearst/MOTOR Information Systems will be the best and last place you'll ever work!

Required Experience (Must Have)

  • Expert Python Developer

  • Strong SQL Developer

  • Strong AWS Experience (Lambda, Glue, State Machines, Fargate, Cloud Formation, RedShift)

  • Strong Experience with Semi-Structured Data (XML, CSV, JSON, Parquet)

  • Strong Automation Experience 

  • Experience with Databricks (Delta Lake, Notebooks, SQL Analytics) 

  • Experience with Kubernetes (Cluster Orchestration, Container Networking, Pod Management)

  • Experience with DevOps, CI/CD, Deployment Orchestration (Octopus Deploy)

  • Experience with Git and Azure DevOps

  • Experience with Agentic AI (LangGraph, MCP Servers, Agent Frameworks)

  • Experience with Data Handling (Pandas / NumPy, Apache Spark, Ray)

Helpful Experience (Nice to Have)

  • Experience with LLMs, Machine Learning & Deep Learning Libraries, AI Application Frameworks, Vector Databases

  • Experience with Automotive Data / Industry

  • Experience with Agile / Scrum

Primary Responsibilities

  • Analyze large, and complex, data sets
  • Design, develop and coordinate the generation of Data Pipelines
  • Work collaboratively with team to plan and solve complex problems
  • Design for, or optimize existing pipelines, for performance and cost

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