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

MDAEdge

Lead Data Scientist - AWS Certified

Houston, TX · On-site

... data science tools and vendors. • Ensure compliance with organizational standards and policies. • Support team growth by mentoring, coaching, and professional development. • Deliver excellent ...

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How much do data science intern jobs pay per hour?

As of May 30, 2026, the average hourly pay for data science intern in Spring, TX is $20.03, according to ZipRecruiter salary data. Most workers in this role earn between $15.38 and $21.83 per hour, depending on experience, location, and employer.

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.

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 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.
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Data Science Intern jobs near you
Lead Data Scientist(Oil and Gas Industry)

Lead Data Scientist(Oil and Gas Industry)

Tiger Analytics Inc.

Houston, TX

Full-time

Posted 28 days ago

Job description

Tiger Analytics is looking for experienced Data Scientists to join our fast-growing advanced analytics consulting firm. Our consultants bring deep expertise in Data Science, Machine Learning and AI. We are the trusted analytics partner for multiple Fortune 500 companies, enabling them to generate business value from data. Our business value and leadership has been recognized by various market research firms, including Forrester and Gartner. We are looking for top-notch talent as we continue to build the best global analytics consulting team in the world.

We are seeking a Data Scientist with strong downstream refining experience to drive data-driven insights across refinery operations, economics, and reliability. This role partners closely with process engineers, operations, planning, maintenance, and commercial teams to optimize refinery performance using advanced analytics, machine learning, and domain-informed modeling.

You'll work on high-impact problems such as yield optimization, energy efficiency, unit reliability, predictive maintenance, and margin improvement-turning complex refinery data into actionable intelligence.

Key Responsibilities

Analytics & Modeling

  • Develop, validate, and deploy statistical, ML, and optimization models for refining operations
  • Build models supporting:
    • Unit performance optimization (e.g., CDU/VDU, hydrotreating, cracking)
    • Energy efficiency and utilities optimization
    • Yield and cut-point optimization
    • Predictive maintenance and reliability analytics
    • Fouling, corrosion, and anomaly detection
    • Apply time-series analysis to high-frequency plant data (DCS, historian)

Refining Domain Collaboration

  • Partner with process engineers, operations, maintenance, and planning teams to translate refinery problems into analytical solutions
  • Incorporate first-principles knowledge (mass & energy balances, constraints, process limits) into data models
  • Interpret model results in the context of refinery economics, safety, and operability

Communication & Impact

  • Clearly communicate insights to technical and non-technical stakeholders
  • Quantify business impact (margin improvement, energy reduction, reliability gains)

Requirements

  • Bachelor's or Master's degree in Data Science, Chemical Engineering, Applied Mathematics, Statistics, or related field
  • 3-8+ years of experience applying data science in downstream refining or closely related process industries
  • Strong proficiency in Python or R for data analysis and modeling
  • Experience with time-series data and industrial process data
  • Solid understanding of refining processes and unit operations
  • Experience working with historians (PI), SQL databases, and unstructured data

Preferred Qualifications

  • Advanced degree (MS or PhD)
  • Familiarity with:

Optimization techniques (LP/NLP)

Digital twin or hybrid physics + ML models

Cloud platforms (AWS, Azure, GCP)nced Data Scientists.

Benefits

This position offers an excellent opportunity for significant career development in a fast-growing and challenging entrepreneurial environment with a high degree of individual responsibility.

Tiger Analytics provides equal employment opportunities to applicants and employees without regard to race, color, religion, age, sex, sexual orientation, gender identity/expression, pregnancy, national origin, ancestry, marital status, protected veteran status, disability status, or any other basis as protected by federal, state, or local law.

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