Senior Research Scientist, AI's Impact on the Software Development Life Cycle

• Take nebulous socio-technical AI impact questions and turn them into concrete, validated, measurement strategies. Scale research strategies through Data Science and UXR partnerships.
  
• Apply causal frameworks (e.g., difference-in-differences, instrumental variables, regression discontinuity, synthetic controls, quasi-experiments) to understand AI impact from observational and behavioral data.
• Advise Product areas and Product teams on data driven system improvements e.g., how to better utilize AI in the software development lifecycle, how to improve product strategy to meet new development approaches, etc.
• Mentor junior quantitative researchers and data scientists, establishing best practices for statistical inference, study design, and empirical reproducibility.

Minimum qualifications:

• PhD degree in Economics, Computer Science, Machine Learning, or a related field.
• 2 years of experience leading a research agenda.
• One or more publications in an economics or AI journal or conference (such as the ICSE or FSE).

Preferred qualifications:

• Applied experience with NLP/LLM frameworks (e.g., embeddings, text classification, prompt engineering, fine-tuning/distillation) applied to quantitative research or social science problems.
• Demonstrated proficiency in Python and standard scientific computing/ML libraries (pandas, NumPy, PyTorch/JAX, scikit-learn, statsmodels).
• Deep theoretical and practical expertise in causal inference, experimental and quasi-experimental design, and econometrics.
• Track record of developing ML solutions for real world problems.

• PhD degree in Economics, Computer Science, Machine Learning, or a related field.
• 2 years of experience leading a research agenda.
• One or more publications in an economics or AI journal or conference (such as the ICSE or FSE).