ZipRecruiter

Log In

2

Entry Level Data Scientist Machine Learning Jobs in Houston, TX

Crowe LLP

Machine Learning Intern

The Woodlands, TX · On-site

$27 - $42/hr

Role Summary The data science (DS) internship at Crowe follows the firmwide calendar, approximately overlapping the academic summer. DS interns will have a designated data scientist mentor and will ...

Crowe LLP

Machine Learning Intern

Houston, TX · On-site

$27 - $42/hr

Role Summary The data science (DS) internship at Crowe follows the firmwide calendar, approximately overlapping the academic summer. DS interns will have a designated data scientist mentor and will ...

Varsity Tutors

Data Science Tutor

Missouri City, TX · Remote

$18 - $40/hr

What We Look For In a Data Science Tutor * Advanced Subject Mastery ... Deep knowledge of statistical analysis, data wrangling, exploratory data analysis, machine learning ...

Varsity Tutors

Data Science Tutor

Pearland, TX · Remote

$18 - $40/hr

What We Look For In a Data Science Tutor * Advanced Subject Mastery ... Deep knowledge of statistical analysis, data wrangling, exploratory data analysis, machine learning ...

Varsity Tutors

Data Science Tutor

Sugar Land, TX · Remote

$18 - $40/hr

What We Look For In a Data Science Tutor * Advanced Subject Mastery ... Deep knowledge of statistical analysis, data wrangling, exploratory data analysis, machine learning ...

Varsity Tutors

Data Science Tutor

Houston, TX · Remote

$18 - $40/hr

What We Look For In a Data Science Tutor * Advanced Subject Mastery ... Deep knowledge of statistical analysis, data wrangling, exploratory data analysis, machine learning ...

previous page

Showing results 41-60

All JobsData Scientist Machine Learning JobsEntry Level Data Scientist Machine Learning JobsEntry Level Data Scientist Machine Learning Jobs in Houston, TX

Entry Level Data Scientist Machine Learning information

See Houston, TX salary details

$35.8K

$117.2K

$187.7K

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

As of Sep 6, 2026, the average yearly pay for entry level data scientist machine learning in Houston, TX is $117,212.00, according to ZipRecruiter salary data. Most workers in this role earn between $94,100.00 and $129,900.00 per year, depending on experience, location, and employer.

What is an entry level data scientist machine learning?

Entry level data scientist machine learning jobs are positions for individuals who are new to the field of data science and machine learning. These roles typically focus on working with data, building and testing machine learning models, and supporting more experienced data scientists. Entry level professionals may clean and analyze data, implement basic algorithms, and help interpret results to inform business decisions. These jobs often require proficiency in programming languages like Python or R, foundational knowledge of statistics, and some experience with machine learning libraries.

What are the key skills and qualifications needed to thrive as an entry level data scientist machine learning?

To thrive as an Entry Level Data Scientist in Machine Learning, you need a solid background in statistics, programming (Python or R), and foundational machine learning concepts, typically supported by a relevant degree in computer science, data science, or a related field. Familiarity with tools and libraries such as scikit-learn, TensorFlow, Pandas, and SQL, as well as experience with data visualization platforms, is highly valuable. Strong problem-solving skills, attention to detail, and the ability to communicate technical findings clearly set candidates apart. These skills are essential for effectively analyzing data, building predictive models, and translating complex results into actionable business insights.

What are some common challenges faced by entry level data scientists working with machine learning models?

Entry-level data scientists often encounter challenges such as cleaning and preparing messy or incomplete datasets, selecting appropriate algorithms for specific problems, and tuning model parameters to achieve optimal performance. In addition, they may need to clearly communicate technical findings to non-technical stakeholders and collaborate closely with team members from engineering, product, and business departments. Gaining experience in version control, reproducibility, and model deployment are also important steps in mastering the end-to-end machine learning workflow.

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

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

What are popular job titles related to Entry Level Data Scientist Machine Learning jobs in Houston, TX?

For Entry Level Data Scientist Machine Learning jobs in Houston, TX, the most frequently searched job titles are:

What job categories do people searching Entry Level Data Scientist Machine Learning jobs in Houston, TX look for?

The top searched job categories for Entry Level Data Scientist Machine Learning jobs in Houston, TX are:

What cities near Houston, TX are hiring for Entry Level Data Scientist Machine Learning jobs?

Cities near Houston, TX with the most Entry Level Data Scientist Machine Learning job openings:

Entry Level Data Scientist Machine Learning jobs near you
Infographic showing various Entry Level Data Scientist Machine Learning job openings in Houston, TX as of August 2026, with employment types broken down into 1% As Needed, 84% Full Time, 12% Part Time, and 3% Contract. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution, with an average salary of $117,212 per year, or $56.4 per hour.

Data Scientist Enterprise Reporting & Analytics

iSphere Innovation Partners, LLC

The Woodlands, TX

Full-time

Posted 16 days ago

Job description

Data Scientist – Enterprise Reporting & Analytics
Spring, TX | Hybrid | Must Live Within 50 Miles of Spring | Full-Time

iSphere is looking for a Data Scientist who can help a financial services organization get out of the cycle of scattered reports, conflicting numbers, and business users needing IT every time they want an answer.

This is not a pure machine learning role. The focus is much more practical: centralizing enterprise reporting, creating trusted datasets, improving access to data, and giving business users the ability to handle more of their own reporting and analytics.

You will work across data lakes, enterprise data platforms, reporting tools, and business teams to help build a more consistent reporting environment. That includes identifying duplicate or outdated reports, standardizing business metrics, creating reusable datasets and semantic models, and helping move reporting away from spreadsheets and one-off solutions.

A big part of this role is understanding how data moves from source systems into centralized platforms and then into the hands of business users. You should be comfortable working with both the technical side of the data environment and the people who actually need to use it.

What we need:

  • Strong experience working with enterprise data and analytics environments
  • Hands-on experience with data lakes, enterprise data warehouses, or modern cloud data platforms
  • Advanced SQL skills with the ability to work across large and complex datasets
  • Experience building self-service reporting and analytics environments
  • Experience centralizing or consolidating reporting across multiple departments or systems
  • Strong experience with Power BI, Tableau, or similar enterprise BI tools
  • Experience creating reusable datasets, data models, semantic layers, or curated reporting structures
  • Strong understanding of data quality, data modeling, reporting architecture, and governance
  • Ability to gather requirements directly from business stakeholders and turn them into scalable data solutions
  • Strong communication skills with the ability to explain technical data concepts without making everyone else regret joining the meeting

Experience in banking or financial services would be a big plus, especially if you have worked with customer, deposit, loan, transaction, risk, finance, or regulatory reporting data.

Experience with Azure, AWS, Snowflake, Databricks, Python, metadata management, data cataloging, or enterprise data modernization will also get our attention.

The client is especially interested in someone who has already lived through this kind of transformation. Maybe reporting was spread across departments, everybody had their own spreadsheet, and three people could produce three different versions of the same number. You helped bring that environment together, create trusted data sources, and give the business better access without creating a new ticket every time someone wanted a report.

If you enjoy turning fragmented data into something people can actually trust and use, this could be a great fit.