Postdoctoral Fellow, Digital, Data, and Design Institute - Digital Reskilling Lab

Details

Title Postdoctoral Fellow, Digital, Data, and Design Institute - Digital Reskilling Lab

School Harvard Business School

Department/Area

Position Description

The Digital Reskilling Lab, led by Professors Raffaella Sadun and Jorge Tamayo, is seeking a Postdoctoral Fellow. The mission of the Digital Reskilling Lab is to conduct research on workplace initiatives aimed at retraining and reskilling employees, whose jobs are being replaced by digital technologies. The Lab partners with organizations to test the feasibility, scalability, and effectiveness of different approaches to the skills challenge. An ideal candidate will be interested in conducting cutting edge research on reskilling initiatives both with the PIs and autonomously, and will be proficient in advanced econometric techniques, leveraging large datasets.

The Postdoctoral Fellow reports directly to faculty in the Digital Reskilling Lab and administrative manager in the Research Staff Services office.

Position Description:

A typical empirical project involves refining a research question, designing an experiment or survey, analyzing historical and experimental data, and writing for peer reviewed social science journals. Candidates should have some familiarity with:

• Causal analysis and experimental design: difference-in-differences and fixed effects models, instrumental variables, treatment selection, power analysis, analysis of attrition and non-compliance, analysis of heterogeneous effects and interference;

• Designing lab experiments, field experiments, and/or surveys;

• Programming/scripting knowledge suitable for processing raw data for analysis (e.g., text manipulation);

• One or more computational environments for statistical analysis (e.g., MATLAB , Stata, R, or Python);

• Creating and managing very large datasets;

• Managing and mentoring research assistants (RAs);

• Machine learning skills;

• Writing papers for management and economics journals;

• Interest in reskilling initiatives;

• Working with partner organizations or companies.

Basic Qualifications

• A Ph.D. in economics or related discipline.

• Proficiency in the use of large datasets using SQL , AWS , Snowflake.

• Strong team player with excellent verbal and written communication skills

• Ability to build trust and collaboration by being present on-site and engaging directly with colleagues and various constituents.

PLEASE NOTE : If you have obtained your Ph.D. in the past 12 months you must be able to provide a certificate of completion from the degree-granting institution OR a letter from the institution's Registrar stating all requirements for the degree have been successfully completed and should verify the date the degree has been conferred. No exceptions.

Additional Qualifications

Special Instructions

Applications will be accepted until the position is filled. Please do not contact lab faculty; if you have any questions, please contact [email protected].

All applications should include the following:

• Curriculum vitae

• Copy of academic records (unofficial records are acceptable)

• 2-page research statement

• Two research papers

• Contact details of at least two references

Candidates may be asked to undergo an assessment as part of the interview process.

Additional Information:

These are term positions starting July 2026 (start date flexible) through June 30, 2027, with the possibility of renewal based on funding and performance. Relocation funding not provided.

This role is offered as a hybrid (some combination of onsite and remote) where you are required to be onsite at our Boston, MA based campus. Specific days and schedule will be determined between you and your manager.

Please note that we will be conducting interviews virtually (phone and/or Zoom) for selected candidates.

Contact Information

Kate de Stadler

Recruiting Manager, Research Staff Services

HARVARD | BUSINESS | SCHOOL

Contact Email [email protected]

Salary Range

$75,000 annually

Minimum Number of References Required 2

Maximum Number of References Allowed 4

Keywords

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Supplemental Questions