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New Grad Machine Learning Jobs in Dayton, TX (NOW HIRING)

WorkNovas LLC

Senior Data Scientist

Houston, TX · On-site

This requires that you have next to your knowledge of machine learning and/or statistics a good ... Learning new engineering practices, technologies and continuously improving our Agile practices ...

Pwc

AI Engineer

Houston, TX

$50K - $112K/yr

... new technologies and methodologies in AI engineering What You Must Have - At least a Bachelor ... Certifications aligned to data engineering, machine learning, and cloud platforms, including AWS ...

Deloitte

Senior AI Engineer - SFL Scientific

Houston, TX · On-site

$99K - $137K/yr

Work with clients to design, develop, and deploy new architectures to support machine learning & automation applications * Leverage advanced technical skills in modern data architecture, data science ...

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Showing results 41-60

All JobsNew Grad Machine Learning JobsNew Grad Machine Learning Jobs in Dayton, TX

New Grad Machine Learning information

See Dayton, TX salary details

$25K

$41.7K

$86.2K

How much do new grad machine learning jobs pay per year?

As of Sep 2, 2026, the average yearly pay for new grad machine learning in Dayton, TX is $41,692.00, according to ZipRecruiter salary data. Most workers in this role earn between $31,800.00 and $45,000.00 per year, depending on experience, location, and employer.

What is a new grad machine learning?

New Grad Machine Learning roles are entry-level positions designed for recent graduates who have studied machine learning, artificial intelligence, data science, or related fields. These positions typically involve working with experienced data scientists and engineers to develop, implement, and improve machine learning models and algorithms. New grads in these roles often contribute to projects involving data preprocessing, model training, evaluation, and deployment. The goal is to help new graduates gain hands-on experience and grow their skills in a real-world setting while contributing to the organization's AI initiatives.

What skills and qualifications are needed to thrive as a new grad machine learning?

To thrive as a New Grad Machine Learning Engineer, you need a solid foundation in mathematics, statistics, and programming (especially Python), typically supported by a degree in computer science or a related field. Familiarity with machine learning frameworks such as TensorFlow or PyTorch, version control systems like Git, and coursework or certification in data science are highly beneficial. Strong problem-solving abilities, curiosity, and effective communication skills help you collaborate and convey complex technical concepts to diverse teams. These skills and qualities are essential for developing innovative models, ensuring project success, and integrating seamlessly into fast-paced tech environments.

What challenges do new graduates face when starting out in a machine learning role, and how can they overcome them?

New grad machine learning engineers often encounter challenges such as bridging the gap between academic knowledge and practical, production-level projects. Adapting to real-world data issues, collaborating with cross-functional teams, and understanding scalable deployment can be daunting at first. To overcome these, it's helpful to seek mentorship, proactively ask questions, and dedicate time to learning best practices in code versioning, model evaluation, and team communication. Engaging in code reviews and participating in team discussions can also accelerate the learning curve and foster professional growth.

What is the difference between New Grad Machine Learning vs Data Scientist?

AspectNew Grad Machine LearningData Scientist
Required CredentialsBachelor's in CS, Data Science, or related field; some internshipsBachelor's or Master's in CS, Statistics, or related; some experience
Work EnvironmentEntry-level, team-focused, research and developmentData analysis, modeling, cross-functional collaboration
Employer & Industry UsageTech companies, startups, research labsTech, finance, healthcare, consulting firms

New Grad Machine Learning roles typically focus on foundational skills, internships, and entry-level tasks, while Data Scientist positions often require more experience in data analysis and statistical modeling. Both roles are common in tech industries, but Data Scientists usually handle broader data analysis responsibilities.

What cities near Dayton, TX are hiring for New Grad Machine Learning jobs?

Cities near Dayton, TX with the most New Grad Machine Learning job openings:

New Grad Machine Learning jobs near you

Senior Data Scientist

WorkNovas LLC

Houston, TX • On-site

Contractor

Re-posted 6 days ago

Job description

Senior Data Scientist
Houston, TX
Description: 

We are looking for a candidate with the ability to translate a business question into a data science solution. This requires that you have next to your knowledge of machine learning and/or statistics a good grasp of software development. Next to the data science capabilities and experiences you should be able to clearly and effectively present findings to our colleagues in other areas of expertise and business stakeholders.

The ideal candidate has strong background in quantitative skills (like statistics, mathematics, advanced computing, machine learning) and has applied those skills in solving real world problems across different businesses / functions.

Accountabilities:

• Developing data science solutions to business challenges.

• Write clean and maintainable production-level code, including tests; the tech stack we work with includes Python, Databricks, GIT, Azure, SQL.

• Integrating models into production on a weekly or even daily basis

• Work closely with the customer and the Product Owner day-to-day

• Work in a highly-collaborative, friendly Agile environment, participate in Ceremonies and Continuous Improvement activities.

• Documenting and explaining the results of analysis or modelling to both a technical and non-technical audience

• Learning new engineering practices, technologies and continuously improving our Agile practices

Special Challenges:

• Rapid onboarding on projects, understanding analytics goal and working with ill-defined datasets

• Communicating technical jargon in plain English to colleagues within Data Science team and outside Virtual working with network of colleagues located throughout the globe

Skills & Requirements:

• Experience on data science projects.

• Broad experience and knowledge in Statistics, Machine Learning and data engineering.

• Awareness of issues in statistics and dependence on data quality

• A practical approach to problem solving and attention to detail.

• Passion for and expertise in practicing data science to solve real-world customer problems.

• Excellent oral and written communication skills.

• Strong interpersonal skills and enthusiasm for teamwork, as well as the ability to work independently.

• High standards of code quality, making use of version control tools.

• Proficiency in statistical software packages such as R, Python, Matlab.

• Good knowledge of cloud environment like specifically Azure is required.

• Experience in Agile working methodology

 - Software Configuration Management - Knowledge

 - Software Construction - Knowledge

 - Software Engineering Economics - Knowledge