Research and Data Science Fellow – People & Organization

Who You'll Work With

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 flexible scheduling, requiring a minimum commitment of 20 hours per week. The program duration ranges from a minimum of three months to a maximum of one year.

Your Impact

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.

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.

Your Qualifications and Skills

• Currently enrolled in or recently graduated from an advanced degree program (PhD, DPhil, master's) in industrial-organizational (I-O) psychology, organizational behavior, labor or behavioral economics, data science, computer science, engineering 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)
• 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)
• Proven record of leadership in a work setting and/or through extracurricular activities
• 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 in developing, fine-tuning, and deploying neural network architectures using state-of-the-art technologies (PySpark, TensorFlow, PyTorch, Hugging Face)
• Adept at writing efficient, well-documented SQL, with an emphasis on creating scalable and maintainable code
• Familiarity with cloud-based data storage and data analytics tools (e.g., AWS, Azure, Google Cloud)

Who You'll Work With

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 flexible scheduling, requiring a minimum commitment of 20 hours per week. The program duration ranges from a minimum of three months to a maximum of one year.

Your Impact

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.

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.

Your Qualifications and Skills

• Currently enrolled in or recently graduated from an advanced degree program (PhD, DPhil, master's) in industrial-organizational (I-O) psychology, organizational behavior, labor or behavioral economics, data science, computer science, engineering 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)
• 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)
• Proven record of leadership in a work setting and/or through extracurricular activities
• 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 in developing, fine-tuning, and deploying neural network architectures using state-of-the-art technologies (PySpark, TensorFlow, PyTorch, Hugging Face)
• Adept at writing efficient, well-documented SQL, with an emphasis on creating scalable and maintainable code
• Familiarity with cloud-based data storage and data analytics tools (e.g., AWS, Azure, Google Cloud)