The International Council on Clean Transportation (ICCT) is an award-winning, independent, global, non-profit research organization that provides data-driven research to advance policies that reduce the health and environmental impacts of the transportation sector. The ICCT offers a mission-driven and culturally diverse workplace where intelligence, flexibility, transparency, and good humor are highly valued. Join our team of more than 180 talented researchers and support staff with offices in Washington D.C., San Francisco, Berlin, Beijing, New Delhi and São Paulo.

The ICCT is seeking a Student Assistant (in German: "Werkstudent*in") to join the modeling team in our Berlin office. This position provides a unique opportunity to develop quantitative modeling tools that enable cutting-edge research with real-world impact.
If you are a student in the later stages of a Bachelor's degree or enrolled in a Master's program with strong programming and data analysis skills, and you want to address two of the world's most pressing environmental problems — air pollution and climate change — then this is a position you should consider. You will report to a Model Developer in ICCT's Modeling Center. 

You will:

• Develop and adapt Python code across ICCT's suite of models, spanning topics such as vehicle emissions, economics, and charging infrastructure, with guidance from the team

• Prepare, quality-check, and integrate the input datasets our models rely on

• Help run models and visualize and interpret the results

• Contribute to published model documentation 

• Follow the team's software development practices

• Learn about and contribute to research projects that quantify the potential impacts of transportation policies on pollutant emissions, energy consumption, air quality, health, or societal costs

You have:

• Ongoing studies and a strong academic record in data science, computer science, physics, engineering, or related field (university enrollment is a requirement)

• Interest in vehicle technology, climate change, air quality, energy, environment, public health, or related topics  

• Superior proficiency in data analysis with Python (pandas, scipy, numpy, matplotlib) 

• Strong command of common dataframe operations (e.g., group, merge, pivot, melt, filter, fill) 

• Proficiency in Microsoft Office, including Excel 

• Strong interpersonal and English communication skills, both written and verbal  

The following are desireable, but not required: 

• Experience authoring and documenting complex software (e.g., with multiple scripts, packages, interfaces) 

• Familiarity with environmental and energy challenges in the transportation sector 

• Experience working with software version control tools (e.g., Git, GitHub) 

• Familiarity with PyCharm or other Python IDEs (e.g., VS Code) 

• Proficiency in data visualization tools (e.g., Tableau) 

This is a part-time position (10–20 hours/week) in parallel to your university studies. The initial contract runs for one year, with the option to extend depending on team needs and performance. You will work from our Berlin office, close to Bahnhof Zoologischer Garten.
The hourly remuneration is €16-18 depending on experience and level of education.

To apply, please submit (1) a cover letter describing your interest, qualifications, and earliest available start date, (2) a resume, (3) the names and contact information of two professional or academic references, and (4) a Python code sample (single script or GitHub repository containing Python code) primarily authored by you that highlights your fluency in data analysis, code organization, and documentation (e.g., comments and docstrings). The code sample should be unique and reasonably complex, with multiple scripts or functions; please do not include boilerplate code from a course assignment. Incomplete applications will be given less priority. The position will remain open until it is filled. 

We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender, or gender identity or expression. We are proud to be an equal opportunity workplace.