Data Science Intern

Overview

Put your passion and skills to work for the planet. Climate change is the most urgent issue of our time, and we need people like you to help us build a vital Earth — for everyone.

We’re Environmental Defense Fund, a fast-paced nonprofit with a growing staff of more than 1,000 people in nearly 30 countries. We deliver game-changing solutions that cut climate pollution and strengthen people’s ability to thrive despite the effects climate change is already having. We work wherever we can have the most impact, from local communities to top companies to governments worldwide, and even in space.

Our culture, values and commitment to diversity make EDF an exciting and meaningful place to work. Every job here makes a difference. Won’t you join us?

Responsibilities

Program/Department Overview

The Office of Chief Scientist (OCS) is the science hub at EDF, ensuring that the natural and social science that is the backbone for all EDF policy positions is based on the best available information. OCS provides programmatic support for all scientists at EDF in the form of translating basic and applied research into actionable ideas. OCS also fosters relationships with scientists outside the organization.

Within OCS, the intern will report to the VoLo Senior Environmental Data Scientist and Petrochemicals Senior Data Analyst, both of whom are part of EDF’s cross-program Petrochemicals Initiative. EDF’s Petrochemicals initiative seeks to improve the wellbeing of communities living within industrial corridors through community driven solutions. Working with diverse partners, we are advancing scientific and policy tools to support solutions that deliver cleaner air and healthier communities.

Overall Function

Newly accessible environmental data sources with unstructured text fields potentially hold a rich trove of information on root causes of air pollution and pathways to solutions that could reduce emissions. However, scientists, advocates and other stakeholders have not been able to leverage this information for decision-making because text descriptions of events and prevention/mitigation strategies are not standardized or structured, have limited metadata and lack a shared vocabulary.

This project seeks an intern with a computer science background to pilot Natural Language Processing (NLP) analyses for new insights into root causes of air pollution and available prevention/mitigation strategies. The intern will become familiar with two text rich data sources: EPA’s Pollution Prevention (P2) database and TCEQ’s STEERS database, meet with EDF science and policy/legal staff to gain insights on policy relevant data and use cases and build relationships with diverse stakeholders within the organization. Based on this input, the intern will identify NLP software options, select appropriate tools for the project and use natural language processing algorithms to evaluate the data and make inferences about air pollution sources and solutions.

Key Responsibilities

Tasks will include but are not limited to:

• Review NLP software/toolkit options (e.g. python NLTK, R tidytext) and recommend a tech stack for the pilot.
• Familiarize with EPA’s Pollution Prevention (P2) database and TCEQ’s Air Emission Event Report database.
• Survey our internal petrochemical team’s policy use cases and needs for the data.
• Support in developing programs to parse, standardize, clean, and summarize large unstructured text data, e.g. tokenizing, tagging, classifying, grouping, and counting.
• Support in synthesizing findings into recommendations and limitations.
• Prepare final report.
• Present work to technical and non-technical audiences.
• Participate in advancing EDF Diversity, Equity, and Inclusion (DEI) goals in which people from all backgrounds and experiences feel connected, included, and empowered to address the environmental and organizational challenges in alignment with EDF values.

Qualifications

• Currently enrolled in or recent graduate of a Masters degree program.
• Coursework in computer science, applied math, linear algebra, or optimization
• Demonstrated interest in environmental science, preferably atmospheric science.
• Proficiency in programming in a scripting language like R .or python.
• Practical experience in natural language processing with an understanding of value-added as well as limitations and trade-offs among different approaches.
• Familiarity with relational databases.
• Familiarity with version control and commitment to writing organized, well-documented code.
• Excellent written and oral communication skills.
• Must be well organized, motivated, and detail-oriented.
• Ability to multi-task, prioritize and meet deadlines.
• Ability to work in a team setting and have the ability to work independently when projects are due.
• Demonstrate self-awareness, cultural competency and inclusivity, and ability to work with colleagues and stakeholders across diverse cultures and backgrounds.
• Demonstrate initiative and problem solving skills.

Location

Hybrid out of Austin, TX or U.S. Remote

Term

12 weeks

Hours

Full-time (35 hours per week)

Compensation

This internship would involve either compensation for work paid at a rate competitive with leading non-profits at $20/hr.

Application Materials

Interested applicants should attach cover letter and resume to the EDF application.

Pay Ranges

We offer a strong total rewards package encompassing competitive salary, robust benefits, and professional development opportunities consistent with a modern global organization. We take into account factors such as candidate experience, skills, training, internal team equity and local norms.

The pay range for this role is shown below.

Please note that pay ranges are country specific. As a result, the stated currency is not meant be converted into any other currency.

Minimum Salary

USD $20.00/Hr.

Maximum Salary

USD $20.00/Hr.

EEO Information

Environmental Defense Fund is an equal opportunity employer where an applicant's qualifications are considered without regard to race, color, religion, sex, national origin, age, disability, veteran status, genetic information, sexual orientation, gender identity or expression, or any other basis prohibited by law.