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We are delighted to announce an opening for a highly skilled and motivated individual to work as a Junior Research Scientist in the NYU Stern Finance group. This is a full-time, in-person predoctoral research assistant position beginning on or before July 2026. The initial contract is for one year, with a potential extension for a second year upon mutual agreement and funding availability. The job will entail close collaboration in all stages of the research process on new and ongoing projects in the fields of banking, behavioral finance, macro-finance, and financial history, under the guidance of Professors Lingxuan Sean Wu and Peter Koudijs.

One half of the position will focus on banking, behavioral finance, and macro-finance. A key topic is how limited attention shapes financial intermediation, particularly in banking. The other half of the position will center on economic and financial history, with research topics including bank regulation, firm bankruptcy rules, and mortgage design. The fellow will work closely with faculty on all stages of research, from data construction and exploratory analysis to preparing academic papers and presentations.

We are looking for intellectually curious, open-minded students who are eager to learn new methods and ideas. We particularly encourage applications from candidates with experience in Computer Science, either through coursework or practical applications.

As part of the interviewing process, selected candidates will be asked to perform a coding task.

Typical responsibilities include:

+ Cleaning, organizing, and analyzing large-scale micro datasets

+ Building and maintaining data pipelines in Python (plus SQL or similar tools for data handling)

+ Applying machine learning and NLP methods to large-scale structured and unstructured data

+ Implementing econometric analyses

+ Preparing tables, figures, and replication materials for academic papers

+ Conducting literature reviews and writing short research memos

+ Assisting with general project and code management (e.g., version control, documentation)

In compliance with NYC’s Pay Transparency Act, the annual base salary range for this position is $51,700-$61,500. New York University considers factors such as (but not limited to) the specific grant funding and the terms of the research grant when extending an offer.

Basic qualifications

+ Bachelor’s or master’s degree (by the start date) in Economics, Finance, Statistics, Data Analytics, Computer Science, or a related field

+ Strong quantitative background and solid training in statistics/econometrics or machine learning

+ Demonstrated programming skills in Python, Stata or R, and SQL

+ High attention to detail and a strong commitment to clean, reproducible code

+ Strong written and spoken English

+ Serious interest in pursuing a PhD in Finance or Economics

Preferred qualifications

+ Prior research assistant experience or completion of an empirical / computational research project (e.g., thesis, capstone, or open-source project)

+ Experience working with large or complex datasets (administrative data, clickstreams, logs, financial data, etc.)

+ Additional coursework or experience in math, statistics, machine learning, or optimization

To apply, please submit:

+ Cover letter (1–2 pages) describing your background, research interests, programming experience (especially with language models / NLP, if applicable), and your earliest possible start date

+ Curriculum vitae (CV)

+ Transcript(s) for all post-secondary degrees (please include unofficial transcripts for most recent coursework if official transcripts are not available yet)

+ One writing sample and an optional coding sample (e.g., thesis, term paper, or research project; code repositories may be mentioned in the CV or cover letter)

+ Contact information for 2~3 references who can speak to your academic and research potential

Please submit your materials via Interfolio.

Deadline: January 15.

For any questions, please email [email protected] and [email protected]

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NYU is an Equal Opportunity Employer and is committed to a policy of equal treatment and opportunity in every aspect of its recruitment and hiring process without regard to age, alienage, caregiver status, childbirth, citizenship status, color, creed, disability, domestic violence victim status, ethnicity, familial status, gender and/or gender identity or expression, marital status, military status, national origin, parental status, partnership status, predisposing genetic characteristics, pregnancy, race, religion, reproductive health decision making, sex, sexual orientation, unemployment status, veteran status, or any other legally protected basis. All interested persons are encouraged to apply for vacant positions at all levels.

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