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Data Science Intern Jobs in McAllen, TX (NOW HIRING)

Lucky Lincoln Gaming

Data Scientist

San Juan, TX · On-site

$95K - $135K/yr

You can tell which questions need a rigorous answer and which need a good-enough answer by Thursday. * 3+ years in data science, analytics engineering, or quantitative analysis with real operational ...

Raba Kistner Inc.

Engineering Student Intern

Mcallen, TX · On-site

$16 - $20.75/hr

Under immediate supervision, the Engineering Student Intern will work on preparing boring logs and inputting laboratory test data and field logs into gINT software program, submitting OneCall ...

Edinburg CISD

Technology Intern

Edinburg, TX

$10/hr

The Technology Intern will assist campus/department with Technology needs (troubleshooting, installing drivers, Wi-Fi, etc.) and with Technology Inventory while providing excellent customer service.

Buckner International

Internship

Donna, TX · On-site

$14.25 - $19/hr

Buckner Internship Community: Buckner Children and Family Services Location: Rio Grande Valley, TX (multiple) Address: 3780 N Bentsen Palm Dr Mission, TX, 39614 Mile 7 Rd Suite 3, Peñitas, TX, and ...

All JobsData Science Intern JobsData Science Intern Jobs in McAllen, TX

Data Science Intern information

See McAllen, TX salary details

$11

$21

$39

How much do data science intern jobs pay per hour?

As of Sep 1, 2026, the average hourly pay for data science intern in McAllen, TX is $21.38, according to ZipRecruiter salary data. Most workers in this role earn between $16.44 and $23.32 per hour, depending on experience, location, and employer.

What does a data science intern do?

A Data Science Intern typically assists with collecting, cleaning, and analyzing data to support business decisions or research. They work under the supervision of experienced data scientists, helping to build and test predictive models, create data visualizations, and present findings. Interns often use programming languages such as Python or R, and tools like SQL, to manipulate data. The role is designed to provide hands-on experience with real-world data science projects and help interns develop technical and analytical skills.

What types of projects can I expect to work on as a data science intern, and how will I collaborate with other team members?

As a Data Science Intern, you can expect to work on a variety of projects such as data cleaning, exploratory data analysis, building predictive models, or assisting with data visualization tasks. You'll often collaborate closely with data scientists, engineers, and sometimes business analysts, participating in team meetings and brainstorming sessions. Interns are usually given clearly defined tasks that contribute to larger projects, allowing you to learn from experienced professionals while making a meaningful impact. Regular check-ins and mentorship are typical, providing you with feedback and professional growth opportunities throughout your internship.

What are the key skills and qualifications needed to thrive as a data science intern, and why are they important?

To thrive as a Data Science Intern, you need a solid grasp of statistics, data analysis, and programming (often in Python or R), typically supported by coursework in computer science, mathematics, or a related field. Familiarity with data visualization tools (like Tableau), machine learning libraries (such as scikit-learn or TensorFlow), and version control systems (like Git) is commonly expected. Strong problem-solving abilities, communication skills, and a willingness to learn help interns collaborate effectively and translate data insights for diverse audiences. These skills and qualities ensure that interns can contribute meaningfully to projects, adapt quickly, and bridge the gap between raw data and actionable business solutions.

Can I get an internship in data science?

Yes, data science internships are available for students and recent graduates interested in gaining practical experience with skills like programming, statistics, and data analysis using tools such as Python or R. Applicants typically need a background in related fields and may be required to complete technical assessments or projects during the application process.

What are the most commonly searched types of Data Science jobs in McAllen, TX?

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Data Science Intern jobs near you
Infographic showing various Data Science Intern job openings in McAllen, TX as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 14% Part Time, and 3% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $44,470 per year, or $21.4 per hour.

Data Scientist

Lucky Lincoln Gaming

San Juan, TX • On-site

$95K - $135K/yr

Full-time

Medical, Dental, Vision, Retirement

Posted 25 days ago

Job description

Job Type
Full-time
Description
Vast builds the operating and financial backbone for fast-growing, cash-intensive businesses, combining hands-on execution with purpose-built software, automation, and AI-enabled workflows. We provide technology-enabled shared services, financial infrastructure, and operational support to partners across the U.S. and Puerto Rico, with deep roots in route gaming and other multi-location businesses. We work execution-first, with accurate books, strong controls, and dependable processes, then build the automation and software that raise the standard for how the back office operates.
About the Role
One of the biggest partners we support is a video gaming terminal route across Illinois: machines in bars, restaurants, and truck stops, serviced by field technicians, collected by dedicated crews, supported by a call center, and run on a platform we build and maintain. Every piece of that operation throws off data, and far less of it gets used than should. This role exists to close that gap. Not by producing more charts, but by turning that data into finished work: dashboards that answer a real question, and worklists that tell a specific person what to do Monday morning.
This is not a reporting desk. If the job becomes "run this query for me," we built it wrong. It is not a research role either. Elegance is nice, but a route that runs two hours shorter is better. You will sit close to the operation and to the product and engineering teams building its platform, and your work ships into that live platform, not beside it, and the highest-value work here will be the things nobody thought to request.
What You'll Own
You will work across a deep, multi-year data estate: 250+ Illinois locations, machine and game-level performance, cash and service routing, technician dispatch, the project pipeline, call center volume, and public state reporting. Far more signal than currently gets used.
  • Finished analysis, not raw ingredients. A clear answer, the reasoning, and a recommendation someone can act on. Not a table dump.
  • Dashboards people open on purpose. Built into the system of record, in our design system, answering questions the regional directors, ops leads, and executives running the route already ask. If nobody opens it twice, it did not work.
  • Worklists, the part we care most about. Ranked, assignable lists: the specific machines, locations, or routes that need attention this week, in priority order, with the recommended move and the value of making it. Underperforming machines, wrong collection cadences, equipment to repair or replace, ground lost to nearby competition. A short list, ordered by impact, that an operator can work through.
  • Models where they earn their keep. Forecasting, route and schedule optimization, anomaly detection, siting and expected-performance models. Applied, not academic. We care about the decision it changes.

What Success Looks Like
  • First 30 days: You know the data model, the metrics, and where the bodies are buried in the data. You have been in the field at least once.
  • First 90 days: At least one dashboard and one worklist in real use, with an owner who relies on it.
  • First year: Decisions across game mix, routing, staffing, and project prioritization are measurably better because of work you initiated, including work nobody asked for.

Requirements
  • A self-starter with an appetite for data. The best version of this hire goes looking: pulls the state's public reporting because they wondered how the operation stacks up, notices a Tuesday-evening pattern nobody asked about and chases it down, shows up to the meeting with the artifact already built. If you need a fully specified ticket before you start, this will be frustrating for both of us.
  • Fluent in the business, not just the numbers. You will talk to regional directors, technicians, collectors, and the call center, then go to the data with a better question.
  • Comfortable in a fast environment where priorities move and data is not always clean. You can tell which questions need a rigorous answer and which need a good-enough answer by Thursday.
  • 3+ years in data science, analytics engineering, or quantitative analysis with real operational impact.
  • Advanced SQL: window functions, CTEs, query tuning, and the judgment to work confidently in messy production data without hand-holding.
  • Data modeling: you can design schemas, define grain, build fact and dimension structures, and turn transactional systems into analysis-ready models.
  • Data warehousing: standing up and maintaining a warehouse or analytical layer, including ETL/ELT pipelines, incremental loads, and data quality checks.
  • Data visualization with a real point of view on chart selection, encoding, and when a number in a box beats a chart entirely.
  • Dashboarding and UI/UX design: layout, hierarchy, filter design, progressive disclosure, and mobile legibility are part of the job, not polish added at the end.
  • Experience in a modern BI or analytics platform (Tableau, Power BI, Looker, Metabase, Superset, Sigma, Quicksight, or comparable). We care that you have shipped and maintained real reporting for real users, not which tool taught you that.
  • Python or R for analysis and modeling (pandas, scikit-learn, or equivalent).
  • Forecasting and time-series analysis: seasonality, day-of-week and hour-of-day demand patterns, and the judgment to know when a trend is signal and when it is noise.
  • Geospatial analysis: clustering, drive-time and distance modeling, coverage and territory analysis. Route or network optimization experience is a strong plus, since routing is core to how the operation runs.
  • Metric definition and stewardship: you can pin down what a metric means, defend the definition, and keep it from quietly forking into three versions across the business.
  • A track record of taking an ambiguous business question and returning a defensible, actionable answer, and explaining a model to someone who will never look at the code.

Highland Holdings and its portfolio companies are equal opportunity employers. We evaluate all qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other characteristic protected by law.
We offer a full suite of benefits, including medical, dental, vision, 401(k) matching, and more.
Salary Description
$95,000-135,000 + Bonus

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