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Data Scientist Machine Learning Jobs in Dallas, TX

Chewy

Senior Data Scientist

Richardson, TX

$109K - $190K/yr

Data Scientist II Our Opportunity We are seeking a hands-on and highly motivated Data Scientist II ... In this role, you will help build AI-powered and machine learning solutions that improve customer ...

Select Minds LLC

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 ...

Lantern

Data Scientist

Dallas, TX · On-site

As a Data Scientist , you will be responsible for assisting our clients envision, design, develop, and deploy machine learning solutions in Microsoft Azure. As part of a small, dynamic team, you will ...

Select Minds LLC

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 ...

Photon

AI/ML Data Scientist | Onsite

Dallas, TX

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

Photon

AI/ML Data Scientist | Onsite

Dallas, TX · On-site

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

Ruri Software Technologies LLC

Data Scientist

Plano, TX · On-site

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 ...

Lantern

Data Scientist

Dallas, TX · On-site

As a Data Scientist , you will be responsible for assisting our clients envision, design, develop, and deploy machine learning solutions in Microsoft Azure. As part of a small, dynamic team, you will ...

Photon

AI/ML Data Scientist

Dallas, TX · On-site

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

Lantern

Data Scientist

Dallas, TX · On-site

As a Data Scientist , you will be responsible for assisting our clients envision, design, develop, and deploy machine learning solutions in Microsoft Azure. As part of a small, dynamic team, you will ...

Toyota

Principal Data Scientist

Plano, TX · On-site

Who we're looking for Toyota's OneTech Data Science and Machine Learning Department is looking for a passionate and highly motivated Principal Data Scientist. The primary responsibility of this role ...

Judge Group, Inc.

Data Scientist - IV

Dallas, TX · On-site

Independently work on data science projects and deliver innovative technical solutions to solve problems and improve business outcomes Be involved in the design and development of machine learning ...

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All JobsData Scientist Machine Learning JobsData Scientist Machine Learning Jobs in Dallas, TX

Data Scientist Machine Learning information

See Dallas, TX salary details

$37.1K

$121.5K

$194.5K

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

As of Aug 9, 2026, the average yearly pay for data scientist machine learning in Dallas, TX is $121,508.00, according to ZipRecruiter salary data. Most workers in this role earn between $97,500.00 and $134,600.00 per year, depending on experience, location, and employer.

What is a data scientist machine learning?

A Data Scientist specializing in Machine Learning (ML) uses statistical methods, algorithms, and computational power to analyze data and create predictive models. They work with large datasets to identify patterns, train machine learning models, and improve decision-making processes. Responsibilities often include data cleaning, feature engineering, model selection, and performance evaluation. They may collaborate with engineers and business teams to deploy models in real-world applications. Strong skills in programming (Python, R), ML frameworks (TensorFlow, Scikit-learn), and data visualization are essential.

What are the key skills and qualifications needed to thrive in the data scientist machine learning position, and why are they important?

To excel as a Data Scientist Machine Learning, you need a strong proficiency in statistics, programming (typically Python or R), and a solid understanding of machine learning algorithms, usually backed by a degree in computer science, mathematics, or a related field. Familiarity with tools such as TensorFlow, scikit-learn, SQL databases, and cloud platforms, as well as certifications in data science or machine learning, is commonly expected. Analytical thinking, problem-solving skills, and effective communication are vital soft skills in this profession. These qualifications combine to drive impactful insights and enable the successful development and deployment of machine learning models in business environments.

What are the typical day-to-day responsibilities of a data scientist machine learning?

On a typical day, a Data Scientist specializing in Machine Learning might gather and preprocess data, design and implement machine learning models, and evaluate their performance to solve real-world problems. They often collaborate with data engineers, software developers, and business stakeholders to translate business objectives into technical solutions and integrate models into existing systems. Other responsibilities can include visualizing data insights, conducting experiments to tune algorithms, and staying current with new developments in the field. The work is highly collaborative and iterative, requiring clear communication with various teams to ensure project goals are met efficiently.

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 Data Scientist Machine Learning jobs in Dallas, TX? For Data Scientist Machine Learning jobs in Dallas, TX, the most frequently searched job titles are:
What job categories do people searching Data Scientist Machine Learning jobs in Dallas, TX look for? The top searched job categories for Data Scientist Machine Learning jobs in Dallas, TX are:
What cities near Dallas, TX are hiring for Data Scientist Machine Learning jobs? Cities near Dallas, TX with the most Data Scientist Machine Learning job openings:
Data Scientist Machine Learning jobs near you
Infographic showing various Data Scientist Machine Learning job openings in Dallas, TX as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 13% Part Time, and 4% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $121,508 per year, or $58.4 per hour.

Sr. Principal Data Scientist / Machine Learning Engineer

Ascentt

Plano, TX • On-site

Full-time

This job post has expired 1 day ago. Applications are no longer accepted.

Job description

Ascentt is building cutting-edge data analytics & AI/ML solutions for global automotive and manufacturing leaders. We turn enterprise data into real-time decisions using advanced machine learning and GenAI. Our team solves hard engineering problems at scale, with real-world industry impact. We're hiring passionate builders to shape the future of industrial intelligence.
Job Summary
We're looking for an exceptionally skilled and experienced Sr. Principal Data Scientist / Machine Learning Engineer to lead and deliver high-impact AI/ML projects across Automotive domain. The ideal candidate will have a deep understanding of data science and machine learning tools, techniques, and algorithms, coupled with a proven track record of successfully leading projects from conception to deployment. This role demands strong client-facing communication skills and the ability to translate complex technical concepts into tangible business value.
Key Responsibilities
  • Technical Leadership & Strategy:
  • Serve as a primary technical expert and thought leader in Data Science and Machine Learning.
  • Define and drive the technical strategy for AI/ML initiatives, identifying high-value opportunities for optimization, predictive analytics, and process improvement across diverse use cases.
  • Architect and oversee the development of robust, scalable, and production-ready DS/ML models and solutions.
  • Stay at the forefront of the latest advancements in DS/ML, especially those applicable to various industries and large-scale data problems.
  • Project Leadership & Delivery:
  • Lead end-to-end DS/ML projects, including requirements gathering, data exploration, model development, validation, deployment, and monitoring.
  • Define project scope, timelines, and deliverables, ensuring successful execution within budget and schedule constraints.
  • Mentor and guide junior and mid-level data scientists and ML engineers, fostering a culture of technical excellence and continuous learning.
  • Drive MLOps best practices for reliable and efficient model deployment and lifecycle management.
  • Client Management & Communication:
  • Act as a trusted advisor to clients and internal stakeholders, understanding their business challenges and translating them into solvable DS/ML problems.
  • Effectively communicate complex analytical findings, model performance, and business recommendations to both technical and non-technical audiences.
  • Manage client expectations, present progress reports, and ensure stakeholder satisfaction.
  • Facilitate workshops and discovery sessions to identify new opportunities for AI/ML adoption.
  • Use Case Development & Problem Solving:
  • Lead the identification, prioritization, and execution of complex AI/ML use cases that drive significant business impact.
  • Apply deep analytical skills to dissect complex problems, derive actionable insights from data, and design innovative solutions.
  • Develop and implement models for:
  • Predictive Analytics: Forecasting, risk assessment, and anomaly detection.
  • Optimization: Improving efficiency, resource allocation, and decision-making.
  • Pattern Recognition: Identifying trends, segments, and relationships within large datasets.
  • Automation: Leveraging ML for intelligent process automation and enhanced operational efficiency.
  • Tool & Algorithm Proficiency:
  • Demonstrated expertise in a wide range of DS/ML tools and platforms (e.g., Python, R, TensorFlow, PyTorch, scikit-learn, Spark, AWS Sagemaker, Azure ML).
  • Deep understanding and practical application of various machine learning algorithms (e.g., supervised, unsupervised, reinforcement learning, deep learning, time series analysis, NLP, computer vision).
  • Proficiency in data manipulation, SQL, and working with large, complex datasets from various sources.

Qualifications
  • Master's or Ph.D. in Data Science, Machine Learning, Computer Science, Engineering, Operations Research, Statistics, or a related quantitative field.
  • 8+ years of progressive experience in Data Science and Machine Learning roles, with at least 3-5 years in a leadership or principal-level capacity.
  • Demonstrated experience leading multiple end-to-end DS/ML projects successfully from concept to production.
  • Proven track record of managing client interactions, presenting technical solutions, and influencing strategic decisions.
  • Expertise in Python programming (NumPy, Pandas, Scikit-learn, Keras/TensorFlow/PyTorch).
  • Strong understanding of statistical modeling, experimental design, and hypothesis testing.
  • Experience with cloud platforms (AWS, Azure, GCP) and MLOps principles.
  • Excellent communication, interpersonal, and presentation skills.

Preferred Qualifications
  • Experience with real-time data processing and streaming analytics.
  • Knowledge of various industry verticals and their unique data challenges (e.g., finance, healthcare, retail, logistics, manufacturing).
  • Experience with large-scale data architectures (e.g., data lakes, data warehouses, distributed computing).
  • Publications or presentations in relevant fields.

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