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Internship Biotech Data Analyst Jobs in Spring, TX

Data Protection, A/SA-Evergreen

Houston, TX · On-site

$84K - $100K/yr

As a Data Protection Senior Analyst, you'll support the delivery of data protection, data ... Prior internship, academic project, or entry-level experience in security or compliance is a plus.

Analyze data to drive decision-making on new features of Wdesk * Suggest new product development ... This internship is primarily a remote opportunity. However, if you are located near one of our ...

Analyze data to drive decision-making on new features of Wdesk * Suggest new product development ... This internship is primarily a remote opportunity. However, if you are located near one of our ...

Digital Analyst Internships

The Woodlands, TX · On-site

$90K - $106K/yr

By submitting your interest, you'll be among the first to know when internship opportunities open ... About Digital Analyst Roles at Danaher Are you passionate about data, customer experience, and ...

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Internship Biotech Data Analyst information

See Spring, TX salary details

$10

$20

$37

How much do internship biotech data analyst jobs pay per hour?

As of Sep 4, 2026, the average hourly pay for internship biotech data analyst 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 does an internship biotech data analyst do?

An Internship Biotech Data Analyst supports research and development teams in biotechnology companies by collecting, processing, and analyzing complex biological data. They use statistical tools and software to interpret experimental results, identify trends, and help drive decision-making in projects such as drug discovery, genomics, or clinical trials. Interns often work alongside experienced data analysts and scientists, gaining hands-on experience with real-world datasets and contributing to ongoing research efforts.

What types of projects or data sets might I work with as an internship biotech data analyst?

As an Internship Biotech Data Analyst, you can expect to work with real-world biological or clinical data, such as genomic sequences, protein structures, or patient trial results. Projects often involve cleaning, analyzing, and visualizing these datasets to support research or product development. You'll likely collaborate closely with scientists, senior analysts, and sometimes software engineers to interpret findings and present actionable insights. This hands-on experience not only strengthens your technical skills but also helps you understand how data analysis drives innovation in the biotech industry.

What are the key skills and qualifications needed to thrive as an internship biotech data analyst, and why are they important?

To thrive as an Internship Biotech Data Analyst, you need a foundation in biology or biotechnology, statistical analysis, and data interpretation, typically gained through coursework or relevant internships. Familiarity with data analysis tools such as Python, R, Excel, and experience with bioinformatics databases or platforms like BLAST is highly beneficial. Strong attention to detail, problem-solving abilities, and effective communication skills make candidates stand out in this role. These competencies are crucial for accurately analyzing complex biological data, supporting research projects, and conveying findings to multidisciplinary teams.

What is the difference between Internship Biotech Data Analyst vs Biotech Data Scientist?

AspectInternship Biotech Data AnalystBiotech Data Scientist
Required CredentialsEnrolled in or recent graduate of related degree (e.g., biology, bioinformatics, data analysis)Advanced degree (Master's or PhD) in data science, bioinformatics, or related fields
Work EnvironmentInternship setting in biotech or pharmaceutical companies, labs, or research institutionsFull-time role in biotech firms, research centers, or biotech startups
Employer & Industry UsageUsed for entry-level training, skill development, and gaining industry experienceUsed for advanced data analysis, modeling, and research projects

The Internship Biotech Data Analyst is an entry-level position focused on gaining practical experience in biotech data analysis, often requiring relevant coursework or a recent degree. In contrast, a Biotech Data Scientist typically holds advanced degrees and performs complex data modeling and research tasks. The internship provides foundational skills, while the data scientist role involves more specialized expertise and responsibilities.

Can a biotechnology student become a data analyst?

Yes, a biotechnology student can become a data analyst by developing skills in data management, statistical analysis, and tools like Excel, SQL, or Python. Gaining knowledge of data visualization and relevant industry applications can also improve job prospects in biotech data analysis roles.

How do I get an internship at a biotech data analyst?

To secure an internship as a biotech data analyst, candidates should have a strong background in biology, data analysis, and programming languages like Python or R. Gaining experience through relevant coursework, certifications, or projects, and applying to internships via company websites or job portals, can improve chances. Strong analytical skills and familiarity with biotech databases and tools are also beneficial.

What are popular job titles related to Internship Biotech Data Analyst jobs in Spring, TX?

For Internship Biotech Data Analyst jobs in Spring, TX, the most frequently searched job titles are:

What cities near Spring, TX are hiring for Internship Biotech Data Analyst jobs?

Cities near Spring, TX with the most Internship Biotech Data Analyst job openings:

Infographic showing various Internship Biotech Data Analyst job openings in Spring, 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 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $41,655 per year, or $20 per hour.

Commodity Trading Analytics Internship Program

Engelhart

Houston, TX

$68K - $100K/yr

Full-time, Internship

Posted 6 days ago


Job description

Commodity Trading Analytics Internship Program

Six-Month Internship: June 15 - December 16, 2027
Houston and NYC (full-time, on site)
Closing Date: September 13, 2026

Salary Range: $68,000 - $100,000 annualised

Engelhart's Internship Program offers a unique opportunity to gain hands-on experience with North American Front Office teams working at the intersection of commodities markets, data, analytics, modelling and trading. Interns will contribute to practical, data-led projects that support commercial decision-making, forecasting, risk analysis and market insight across power, gas, and broader commodity markets. To be eligible for consideration, applicants must have the right to work in the United States for the full duration of the internship and be available to commence their six-month internship on site from June 15, 2027.

The internship opportunities covered by this advert are as follows:

  • Quantitative Development Intern, Houston
  • Quantitative Research Intern, Houston
  • NA Power & Gas Analytics Intern, Houston
  • FTR Analytics Intern, Houston
  • NA Structured Products & Origination Analytics Intern, Houston
  • West Power Analytics Intern, New York

Applicants may indicate areas of particular interest during the process. All roles require strong analytical and technical skills, with opportunities spanning data analysis and visualisation, machine learning, forecasting, financial modelling, statistics/econometrics and quantitative modelling. Final allocation will take into account business need, candidate profile and overall fit.

Please note: annualized salary will depend on location, role requirements and the candidate's overall profile, including educational background, relevant skills and experience. Final compensation will be determined as part of the offer process, and the upper end of the advertised range is expected to apply only in limited cases.

What You Can Expect

  • Hands-on experience on a commodities trading desk, working on analytical projects with real commercial relevance.
  • Exposure to how data, analytics, visualisation, forecasting, machine learning and modelling support trading and commercial decisions across North American power, gas and broader commodity markets.
  • Close learning and mentorship from experienced front office professionals, including direct exposure to desk leadership.
  • A structured six-month internship within a global commodities business, combining cohort-based learning with deep desk integration.

Example Project Areas

Depending on the internship opportunity, projects may include data analysis and visualisation, building models and analytics, improving machine learning models for power prices, gas demand or renewables, working on Monte Carlo simulations and time-series analysis, supporting pricing, valuation, optimisation or portfolio construction problems, developing AI-enabled tools, improving pre-trade pricing or portfolio management of structured origination positions, and producing insights that help inform front office trading and commercial decisions.

Key Responsibilities

  • Work closely with a Houston or New York front office team on data-led projects within North American power and gas, FTR, structured products and origination, or West Power.
  • Analyse large market, trading and fundamental datasets to identify insights that support forecasting, valuation, risk analysis and commercial decision-making.
  • Develop, test or improve analytical tools, models, dashboards or workflows using Python and other relevant tools.
  • Support forecasting, financial modelling, machine learning, statistical/econometric analysis, Monte Carlo simulation or quantitative optimisation activities, depending on desk requirements.
  • Conduct market research and present findings clearly to technical and commercial stakeholders.
  • Contribute to day-to-day desk activity, building practical understanding of how analytics supports trading and portfolio decisions.

About You

Across our 2027 internship program, we are looking for motivated, intellectually curious individuals who are keen to apply strong analytical, quantitative and technical skills to real business challenges in power, gas, renewables and broader commodity markets. You should be comfortable working with data, learning quickly, and collaborating closely with front office teams in a fast-paced trading environment.

The following experiences and skills are essential for application:

  • Strong academic background in a quantitative discipline such as Computer Science, Data Science, Engineering, Physics, Mathematics, Statistics, Economics, Finance or a related STEM field.
  • Strong Python skills, with the ability to analyze, manipulate and interpret complex data sets.
  • Excellent analytical and problem-solving skills, with a structured and detail-oriented approach.
  • Evidence of applying data analysis, coding or quantitative methods to a practical problem, gained through academic projects, internships, research, personal projects or other relevant experience.
  • Demonstrable interest in commodities, power or financial markets, including an ability to discuss relevant market developments, gained through academic study, projects, internships, research or personal interest.
  • Business-level English proficiency.
  • Right to work in the United States for the full duration of the internship.
  • Effective communication skills and a collaborative mindset, with the confidence to work closely with commercial and technical stakeholders.
  • Intellectual curiosity, with the motivation to understand how market fundamentals, data and commercial decisions interact.

The following would be advantageous:

  • Experience with SQL, relational databases, data visualisation, machine learning, AI/LLM tools, Git, financial modelling, advanced Excel/VBA, or working with large market
  • Exposure to forecasting models, valuation, statistics/econometrics, time-series analysis, stochastic modelling, Monte Carlo simulation, optimisation, MILPs or portfolio construction.