Research and Data Science Fellow - People & Organization

Driving lasting impact and building long-term capabilities with our clients is not easy work. You are the kind of person who thrives in a high performance/high reward culture - doing hard things, picking yourself up when you stumble, and having the resilience to try another way forward. In return for your drive, determination, and curiosity, we'll provide the resources, mentorship, and opportunities you need to become a stronger leader faster than you ever thought possible. Your colleagues—at all levels—will invest deeply in your development, just as much as they invest in delivering exceptional results for clients. Every day, you'll receive apprenticeship, coaching, and exposure that will accelerate your growth in ways you won’t find anywhere else. When you join us, you will have: Continuous learning: Our learning and apprenticeship culture, backed by structured programs, is all about helping you grow while creating an environment where feedback is clear, actionable, and focused on your development. The real magic happens when you take the input from others to heart and embrace the fast-paced learning experience, owning your journey. A voice that matters: From day one, we value your ideas and contributions. You’ll make a tangible impact by offering innovative ideas and practical solutions, all while upholding our unwavering commitment to ethics and integrity. We not only encourage diverse perspectives, but they are critical in driving us toward the best possible outcomes. Global community: With colleagues across 65+ countries and over 100 different nationalities, our firm’s diversity fuels creativity and helps us come up with the best solutions for our clients. Plus, you’ll have the opportunity to learn from exceptional colleagues with diverse backgrounds and experiences. World-class benefits: On top of a competitive salary (based on your location, experience, and skills), we provide a comprehensive benefits package to enable holistic well-being for you and your family. You will help develop cutting-edge assets and knowledge on organizational topics and expand existing expertise and solutions in key practice areas including organizational culture & change, people analytics, talent, organizational design, and leadership development. You’ll work in our People and Organizational Performance Practice (POP) North America as part of our global POP Assets team. As part of our global capabilities and knowledge network, you’ll join more than 1,800 knowledge professionals who work alongside our consultants to generate distinctive insights and innovative solutions that meet our clients' unique needs. In a team focused on development and innovation, you will have ample opportunity to receive excellent mentorship to learn and grow, while having freedom to generate and cultivate new ideas. As a member of our POP Assets team, you will play a key role in applying advanced research and data science methods to drive organizational insights at McKinsey in three ways: Asset development and innovation: You will create scalable solutions, assessments, and tools by conducting foundational research, building new models and frameworks, analyzing survey, archival, financial, operational, and HR data, and implementing these solutions at organizations. Client engagement and support: You will partner with senior team members to serve clients on people and organization topics, leveraging your research and data science skills to translate complex data insights into compelling, actionable recommendations. Knowledge development and external publishing: You will author or contribute to seminal knowledge pieces across a variety of topics and publication formats. You will work with senior leaders to test research questions and hypotheses using survey methods and advanced analytics techniques, including predictive modeling and data visualization. This is a paid opportunity with a work schedule of an expected 40 hours, or more on occasion, a week. This role may include travel within the US. The program duration is set at a maximum of one year.

Currently in ABD status or recently graduated from an advanced degree program (PhD or DPhil) in industrial-organizational (I-O) psychology, organizational behavior, labor or behavioral economics, data science, or a related field (e.g., quantitative psychology, educational measurement) with a strong emphasis on research methodology, machine learning, data engineering, artificial intelligence, and/or advanced statistics Excellent research skills, including the ability to complete all components of complex research projects from start to finish (e.g., literature review and synthesis, research and measurement design, data management/cleaning, analysis, interpretation of findings) Deep theoretical and applied expertise in one of the following areas: people analytics, talent, survey and assessment design (including relevant psychometric methods), organizational culture, organizational design, decision science and behavior change, leadership, or quantitative text analysis Strong proficiency manipulating, analyzing, and visualizing data using R or Python Experience with fundamental statistical analyses (e.g., ANOVAs, regressions) and one or more advanced approaches (e.g., machine learning, cluster analyses, factor analysis, IRT, network analysis, HLM, SEM) Proven record of leadership in a work setting and/or through extracurricular activities with the ability to work collaboratively in a team environment and with people at all levels in an organization Ability to balance multiple competing and shifting priorities, as well as staying calm under pressure and the ability to work flexibly Proficiency in using visualization tools and creating interactive dashboards (e.g., PowerBI, Tableau, R Shiny) Experience applying artificial intelligence (AI) and large language models (LLMs) to behavioral, organizational, or workforce research, including the analysis of qualitative and unstructured organizational data (e.g., interviews, open-ended survey responses, employee feedback) Adept at writing efficient, well-documented code (e.g., R, Python, SQL), with an emphasis on creating scalable, reproducible, and maintainable analytical workflows Familiarity with cloud-based data storage and data analytics tools (e.g., AWS, Azure, Google Cloud) Effective communication and presentation skills, particularly the ability to explain complex analytical concepts in a comprehensible manner adapted to different groups of non-technical audiences (e.g. business managers, heads of products, HR leaders)