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Internship Applied Scientist Machine Learning Jobs in Spring, TX

NOV, Inc.

Senior Data Scientist

Houston, TX · On-site

Architect scalable machine learning and forecasting solutions within cloud platforms such as AWS ... Manage and mentor interns, junior data scientists and analysts * Translate advanced analytics ...

Amazon

Data Scientist II - AMZ27028.1

Houston, TX · On-site

$136K - $184K/yr

... machine learning algorithms, genetic algorithms, and neural networks. Validate models against ... Employer will accept a Bachelor's degree or foreign equivalent degree in Statistics, Applied ...

NAVA Software Solutions

Lead Data Scientist

Houston, TX · On-site

... as machine learning, optimization, and cluster analysis. The incumbent will lead and help to ... A master's degree or PhD in Computer Science, Statistics, Applied Mathematics, or a related field ...

Sky Consulting Inc

Data Scientist

Houston, TX · On-site

As a Data Scientist, you will apply strong expertise through the use of machine learning, data mining, and information retrieval to design, prototype, and build next generation advanced analytics ...

Mindlance

Data Scientist

Houston, TX · On-site

They are seeking a Data Scientist with extensive experience in data mining, artificial intelligence, and machine learning to apply advanced analytics in business contexts. Qualifications : Required ...

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All JobsApplied Scientist Machine Learning JobsInternship Applied Scientist Machine Learning JobsInternship Applied Scientist Machine Learning Jobs in Spring, TX

Internship Applied Scientist Machine Learning information

See Spring, TX salary details

$22.7K

$37.9K

$78.3K

How much do internship applied scientist machine learning jobs pay per year?

As of Jul 16, 2026, the average yearly pay for internship applied scientist machine learning in Spring, TX is $37,895.00, according to ZipRecruiter salary data. Most workers in this role earn between $28,900.00 and $40,900.00 per year, depending on experience, location, and employer.

What types of projects do Internship Applied Scientists in Machine Learning typically work on, and how do they contribute to the team's goals?

Internship Applied Scientists in Machine Learning often collaborate with multidisciplinary teams to tackle real-world problems using data-driven approaches. Typical projects might include developing and fine-tuning machine learning models, conducting experiments to validate hypotheses, or assisting in the deployment of algorithms into production systems. Interns are expected to contribute fresh perspectives, help with data preprocessing, and perform thorough model evaluations. Through these projects, interns gain hands-on experience while directly supporting the team's research and product development objectives.

What is the difference between Internship Applied Scientist Machine Learning vs Internship Data Scientist?

AspectInternship Applied Scientist Machine LearningInternship Data Scientist
Required CredentialsRelevant degrees in Computer Science, Data Science, or related fields; knowledge of ML frameworksDegrees in Statistics, Data Science, or related fields; strong analytical skills
Work EnvironmentResearch and development teams, focus on ML model developmentBusiness teams, focus on data analysis and insights
Employer & Industry UsageTech companies, AI-focused organizationsVarious industries including tech, finance, healthcare
Comparison Search IntentUnderstanding roles in ML research and developmentUnderstanding data analysis and business insights roles

Internship Applied Scientist Machine Learning roles focus on developing and applying machine learning models, often in research settings. In contrast, Internship Data Scientist positions emphasize analyzing data to generate insights for business decisions. Both roles require strong analytical skills and relevant educational backgrounds, but they differ in their primary focus and work environment.

What are the key skills and qualifications needed to thrive as an Internship Applied Scientist in Machine Learning, and why are they important?

To thrive as an Internship Applied Scientist in Machine Learning, you need a solid background in mathematics, statistics, and computer science, often supported by coursework or research experience in machine learning and data analysis. Familiarity with tools such as Python, TensorFlow, PyTorch, and experience working with large datasets are highly valued, along with knowledge of version control systems like Git. Strong problem-solving skills, curiosity, and the ability to communicate complex concepts clearly set top candidates apart. These competencies are crucial for effectively designing, implementing, and presenting machine learning solutions that address real-world challenges.

What does an Internship Applied Scientist in Machine Learning do?

An Internship Applied Scientist in Machine Learning works on real-world projects involving the design, development, and evaluation of machine learning models and algorithms. Their responsibilities typically include data analysis, building predictive models, experimenting with new techniques, and collaborating with engineers and researchers to solve complex problems. Interns gain hands-on experience with tools like Python, TensorFlow, or PyTorch, and contribute to advancing the company's AI capabilities. The role requires a strong foundation in mathematics, statistics, and computer science, as well as the ability to communicate findings to both technical and non-technical stakeholders.
What are popular job titles related to Internship Applied Scientist Machine Learning jobs in Spring, TX? For Internship Applied Scientist Machine Learning jobs in Spring, TX, the most frequently searched job titles are:
What job categories do people searching Internship Applied Scientist Machine Learning jobs in Spring, TX look for? The top searched job categories for Internship Applied Scientist Machine Learning jobs in Spring, TX are:
What cities near Spring, TX are hiring for Internship Applied Scientist Machine Learning jobs? Cities near Spring, TX with the most Internship Applied Scientist Machine Learning job openings:
Internship Applied Scientist Machine Learning jobs near you
Infographic showing various Internship Applied Scientist Machine Learning job openings in Spring, TX as of July 2026, with employment types broken down into 75% Full Time, 23% Part Time, 1% Temporary, and 1% Contract. Highlights an 89% Physical, 2% Hybrid, and 9% Remote job distribution, with an average salary of $37,895 per year, or $18.2 per hour.
Senior Data Scientist

Senior Data Scientist

NOV, Inc.

Houston, TX • On-site

Full-time

Re-posted 9 days ago

NOV rating

8.0

Company rating: 8.0 out of 10

Based on 55 frontline employees who took The Breakroom Quiz

150th of 430 rated machine equipment manufacturers

Job description


Reports to: VP Data & Analytics
As a Senior Data Scientist, you will:
  • Partner with business leaders to identify high-value opportunities in areas such as demand planning, capacity/production planning, procurement, and financial forecasting
  • Develop a firm understanding of specific business processes and real-world workflows
  • Work closely with cross-functional teams including domain experts, business analysts, data engineers and software engineers
  • Lead data science initiatives that impact operations globally across multiple business units
  • Define project scope, timelines and deliverables in collaboration with business leaders
  • Architect scalable machine learning and forecasting solutions within cloud platforms such as AWS, Azure, Databricks, and Snowflake
  • Ensure models are production-ready, robust, and maintainable with appropriate monitoring and retraining pipelines
  • Develop standardized methodologies and frameworks to ensure scalability and consistency across diverse environments
  • Ensure compliance with data governance, privacy, and security standards while scaling analytics solutions globally
  • Manage and mentor interns, junior data scientists and analysts
  • Translate advanced analytics results into strategic recommendations for VP and C-level leadership
  • Utilize programming languages such as SQL, Python for data manipulation, analysis and model development

SUGGESTED QUALIFICATIONS
  • Master's degree in a quantitative discipline
  • Five or more years of professional data science experience in manufacturing and/or supply chain environments
  • Hands-on experience working with ERP data and operational processes including order-to-cash, procure-to-pay, and demand-to-deliver
  • Proven ability to communicate complex or technical concepts clearly to both technical and non-technical audiences
  • Advanced proficiency in Python, SQL and PySpark; experience wrangling large relational datasets
  • Deep expertise in machine learning, forecasting and optimization
  • Experience deploying enterprise-scale solutions in cloud environments (AWS experience preferred)
  • Proficient in at least one data visualization library such as Matplotlib, Seaborn, or Plotly
  • Knowledge of Streamlit for building interactive data applications preferred
  • Familiarity with MLOps practices, CI/CD pipelines, and model lifecycle management
  • Demonstrated ability to drive business impact and ROI through analytics
  • Strong track record of executive-level communication and influence
  • Experience leading cross-functional teams across multiple geographies

What NOV employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

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About NOV

Sourced by ZipRecruiter

Throughout every region in the world and across every area of drilling and production, our family of companies has provided the technical expertise, advanced equipment and operational support necessary for success. We have the people, capabilities and vision to serve the needs of a challenging and evolving industry. One the world can’t live without. We are a global family of thousands of individuals, working as one team to create lasting impact for ourselves, our customers and the communities where we live and work. We take responsibility for each other and our company’s future, knowing that personal ownership leads to broader success. We believe in purposeful innovation because we see what others do not and we act. Through business innovation, product creation and service delivery, we are driven to power the industry that powers the world better.

Industry

Oil and gas extraction

Company size

10,000+ Employees

Headquarters location

Houston, TX, US

Year founded

1841

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