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Internship Downstream Process Development Scientist Jobs in Spring, TX

Danaher

R&D Internships

Houston, TX

By submitting your interest, you'll be among the first to know when internship opportunities open ... You'll work in a collaborative environment alongside experienced scientists and contribute to real ...

Danaher

R&D Internships

The Woodlands, TX

By submitting your interest, you'll be among the first to know when internship opportunities open ... You'll work in a collaborative environment alongside experienced scientists and contribute to real ...

Accenture

Energy Downstream Consulting Manager

Houston, TX · On-site

$94.40K - $293.80K/yr

Contribute to business development efforts by identifying opportunities, shaping proposals, and ... Knowledge of work and asset management processes within refining or LNG operations * Prior ...

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$18

$34

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How much do internship downstream process development scientist jobs pay per hour?

As of May 28, 2026, the average hourly pay for internship downstream process development scientist in Spring, TX is $34.41, according to ZipRecruiter salary data. Most workers in this role earn between $25.24 and $41.06 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an Internship Downstream Process Development Scientist, and why are they important?

To thrive as an Internship Downstream Process Development Scientist, you need foundational knowledge in biochemistry, molecular biology, or chemical engineering, often supported by ongoing or recent enrollment in a relevant degree program. Familiarity with laboratory techniques such as chromatography, filtration, and analytical instruments, as well as experience with lab management software, is typically expected. Attention to detail, problem-solving abilities, and effective teamwork are standout soft skills in this role. These skills and qualifications are crucial for conducting reliable experiments, analyzing data, and contributing to the optimization of bioprocesses in a collaborative research environment.

What types of projects and responsibilities can an Internship Downstream Process Development Scientist expect to work on?

As an Internship Downstream Process Development Scientist, you can expect to be involved in hands-on laboratory work focusing on the purification and characterization of biopharmaceutical products. Typical responsibilities include preparing buffer solutions, operating chromatography and filtration systems, analyzing samples using various analytical techniques, and documenting experimental results. Interns often collaborate with experienced scientists and engineers, contributing to process optimization and troubleshooting. The role provides valuable exposure to industry-standard procedures and the opportunity to develop technical skills in a team-oriented environment.

What does an Internship Downstream Process Development Scientist do?

An Internship Downstream Process Development Scientist works in the biopharmaceutical industry, assisting with the development and optimization of processes that purify biological products such as proteins, antibodies, or vaccines after they are produced by cells. Their role often involves supporting laboratory experiments, analyzing samples, and documenting results to improve the efficiency and scalability of downstream processes like filtration and chromatography. Interns in this position gain hands-on experience with cutting-edge technologies and learn about regulatory requirements and industry standards. This role helps prepare students or recent graduates for a career in process development or biomanufacturing.
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Internship Downstream Process Development Scientist jobs near you
Infographic showing various Internship Downstream Process Development Scientist job openings in Spring, TX as of May 2026, with employment types broken down into 2% Internship, 3% As Needed, 19% Full Time, 65% Part Time, 10% Contract, and 1% Nights. Highlights an 77% Physical, and 23% Remote job distribution, with an average salary of $71,565 per year, or $34.4 per hour.
Lead Data Scientist(Oil and Gas Industry)

Lead Data Scientist(Oil and Gas Industry)

Tiger Analytics Inc.

Houston, TX

Full-time

Posted 26 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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