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Temporary Data Scientist Machine Learning Jobs in Dallas, TX

Data Scientist

Dallas, TX · On-site

$65 - $75/hr

Roles & Responsibilities . 6+ years of experience in Machine Learning and Data Science. * Strong understanding of Generative AI, Retrieval Augmented Generation, Agentic Workflow, Statistical methods ...

Data Scientist

Dallas, TX · On-site

$65 - $75/hr

Roles & Responsibilities 6+ years of experience in Machine Learning and Data Science. • Strong understanding of Generative AI, Retrieval Augmented Generation, Agentic Workflow, Statistical methods ...

Translate business problems into well-defined machine learning and predictive modeling objectives. * Collect, clean, transform, and analyze structured and unstructured data from multiple sources.

AI/ML Data Scientist | Onsite

Dallas, TX · On-site

$40 - $140/hr

Translate business problems into well‑defined machine learning and predictive modeling objectives. * Collect, clean, transform, and analyze structured and unstructured data from multiple sources.

Translate business problems into well-defined machine learning and predictive modeling objectives. * Collect, clean, transform, and analyze structured and unstructured data from multiple sources.

Data Scientist Location : Plano, TX, 5900 West Plano Parkway, 75093 About the Role We're looking ... Apply AI and machine learning to improve operations and decision-making * Partner with business and ...

AI/ML Data Scientist Location: Dallas, TX (Onsite) Key Responsibilities ... Translate business problems into well-defined machine learning and predictive modeling objectives.

Expertise in statistical modeling, machine learning, and predictive analytics. * Strong proficiency ... Mentor data scientists and promote best practices in analytics and machine learning. * Support ...

Expertise in statistical modeling, machine learning, and predictive analytics. * Strong proficiency ... Mentor data scientists and promote best practices in analytics and machine learning. * Support ...

Expertise in statistical modeling, machine learning, and predictive analytics. * Strong proficiency ... Mentor data scientists and promote best practices in analytics and machine learning. * Support ...

Expertise in statistical modeling, machine learning, and predictive analytics. * Strong proficiency ... Mentor data scientists and promote best practices in analytics and machine learning. * Support ...

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Temporary Data Scientist Machine Learning information

See Dallas, TX salary details

$37.1K

$121.4K

$194.4K

How much do temporary data scientist machine learning jobs pay per year?

As of Aug 25, 2026, the average yearly pay for temporary data scientist machine learning in Dallas, TX is $121,417.00, according to ZipRecruiter salary data. Most workers in this role earn between $97,400.00 and $134,500.00 per year, depending on experience, location, and employer.

What does a temporary data scientist specializing in machine learning do?

A Temporary Data Scientist specializing in Machine Learning is responsible for designing, building, and deploying machine learning models to analyze data and generate insights, but works on a contract or short-term basis. Their duties often include data preprocessing, model selection and validation, and communicating results to stakeholders. They may also be tasked with automating processes, cleaning large datasets, and collaborating with other teams to implement solutions. The temporary nature of the job means they often focus on specific projects or provide support during peak periods.

What are the key skills and qualifications needed to thrive as a temporary data scientist specializing in machine learning?

To thrive as a Temporary Data Scientist Machine Learning, you generally need a strong background in statistics, programming (Python or R), and experience with machine learning algorithms, often supported by a degree in computer science, mathematics, or a related field. Familiarity with data visualization tools (like Tableau), machine learning libraries (such as scikit-learn, TensorFlow, or PyTorch), and version control systems (e.g., Git) is typically required. Strong problem-solving abilities, adaptability, and effective communication are crucial soft skills for collaborating with teams and translating technical findings to stakeholders. These skills ensure that temporary data scientists can quickly contribute actionable insights, drive data-driven decisions, and add value within a limited time frame.

What are some typical projects or tasks a temporary data scientist specializing in machine learning might work on?

As a temporary Data Scientist focusing on machine learning, you can expect to work on short-term, high-impact projects such as building predictive models, cleaning and preparing data, or developing automated analytics solutions. You may be brought in to support ongoing initiatives, provide expertise for a specific project phase, or help accelerate a backlog of tasks. Collaboration is common, and you'll likely work closely with data engineers, business analysts, and domain experts to understand requirements and deliver actionable insights within tight deadlines. This role offers exposure to diverse datasets and tools, and is an excellent opportunity to rapidly expand your experience and network.

What is the difference between Temporary Data Scientist Machine Learning vs Temporary Data Analyst?

AspectTemporary Data Scientist Machine LearningTemporary Data Analyst
Required CredentialsBachelor's/Master's in Data Science, Computer Science, or related fields; knowledge of ML algorithmsBachelor's in Statistics, Mathematics, or related fields; proficiency in data analysis tools
Work EnvironmentProject-based, collaborative teams, tech-focused companiesBusiness units, reporting teams, data-driven departments
Employer & Industry UsageTech firms, finance, healthcare, e-commerceRetail, marketing, finance, consulting

Temporary Data Scientist Machine Learning roles focus on developing and deploying machine learning models, requiring advanced analytics skills. Temporary Data Analysts primarily interpret data, generate reports, and support decision-making. While both roles involve data handling, Data Scientists with ML expertise work on predictive modeling, whereas Data Analysts focus on descriptive analytics. The choice depends on the project needs and skill requirements.

What are the most commonly searched types of Data Scientist Machine Learning jobs in Dallas, TX?

The most popular types of Data Scientist Machine Learning jobs in Dallas, TX are:

What are popular job titles related to Temporary Data Scientist Machine Learning jobs in Dallas, TX?

For Temporary Data Scientist Machine Learning jobs in Dallas, TX, the most frequently searched job titles are:

What job categories do people searching Temporary Data Scientist Machine Learning jobs in Dallas, TX look for?

The top searched job categories for Temporary Data Scientist Machine Learning jobs in Dallas, TX are:

What cities near Dallas, TX are hiring for Temporary Data Scientist Machine Learning jobs?

Cities near Dallas, TX with the most Temporary Data Scientist Machine Learning job openings:

Infographic showing various Temporary Data Scientist Machine Learning job openings in Dallas, TX as of August 2026, with employment types broken down into 1% As Needed, 85% Full Time, 11% Part Time, and 3% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $121,417 per year, or $58.4 per hour.

Data Scientist

Dallas, TX • On-site

Select Minds LLC
IT Services • 51 - 200 employees

$65 - $75/hr

Full-time

This job post has expired today. Applications are no longer accepted.


Job description

Benefits:
  • HYBRID
  • Competitive salary
  • Opportunity for advancement
  • Training & development

Job Title: Data Scientist – Integrated Operations
Location: Dallas, TX (Hybrid Remote)
In-Person Interview
 Must be authorized to work in the U.S

Work Arrangement
- Hybrid work model: primarily remote within the Dallas–Fort Worth area.
- Occasional on-site presence required for meetings, training, or business needs.
- Limited business travel may be required.
Roles &  Responsibilities
.               6+ years of experience in Machine Learning and Data Science.
•            Strong understanding of Generative AI, Retrieval Augmented Generation, Agentic Workflow, Statistical methods, data structures, and       algorithms.
•            Strong programming skills in Python; experience with Machine Learning libraries and Generative AI frameworks (e.g., Pandas, NumPy, Matplotlib, Seaborn, TensorFlow, PyTorch, scikit-learn, LangChain) and LLMs.
•            Experience developing and deploying AI solutions on cloud platforms (e.g., AWS, Azure, or GCP).
•            Experience in building Asynchronous Python APIs.
•            Experience with data visualization tools such as Matplotlib, Seaborn, or Tableau.
•            Familiarity with cloud platforms such as AWS, Azure, or Google Cloud for deploying AI solutions.
•            Proven experience in developing and deploying machine learning models in a production environment.
•            Experience working with large datasets and performing data analysis
Required Qualifications
Education
- Bachelor's degree in Mathematics, Computer/Data Science, Information Technology, or a related field, or equivalent experience.
Experience
- Advanced experience in data science, machine learning, AI, or optimization projects.
- Proficiency in Python and SQL.
- Strong understanding of statistical methods, experimental design, and model validation.
- Experience with data pipelines and relevant programming libraries (e.g., Pandas, NumPy, Scikit-learn, XGBoost, TensorFlow, Pyspark).
- Familiarity with data visualization tools (e.g., Tableau, Plotly, Streamlit).
Preferred Experience
- Experience with AWS cloud services (e.g., SageMaker, Lambda, Glue, EMR).
- Exposure to specialized analytics areas such as simulation, graph analytics, or video analytics.

Skills & Abilities

- Ability to independently manage and deliver on complex projects.
- Strong problem-solving and critical thinking skills.
- Effective communication skills for both technical and executive audiences.
- Ability to adapt quickly to changing priorities and new technologies.
- Strong interpersonal and collaboration skills.
.....