People Research Scientist (Organizational)

San Francisco, CA

Who We Are

Twitter is the window to the world. Our mission is to give everyone the power to create and share ideas and information instantly, without barriers. We believe the open exchange of information can be a compelling force for good in the world, and have built Twitter to be the real-time public platform for authentic voices, conversations, and ideas. That is what makes Twitter unique.

We are empowered to use our creativity and follow our passions to serve the public conversation and we do it as a global team with smart, talented, and humble people.  The People Analytics team’s vision is to lead in talent insights that enable Twitter to attract, hire, engage, and retain the people who will carry Twitter Forward. 

Key Responsibilities:

     Work closely with Inclusion and Diversity (I&D) along with Learning and Development (L&D) teams to develop, roll-out, and evaluate programs and initiatives. 

     Develop and lead the measurement strategy for I&D and L&D areas including data collection, assessment development, and evaluation.  

     Analyze data to identify insights make actionable recommendations, identify outliers, and set targets within the I&D and L&D spaces. 

     Clean and evaluate employee data (e.g., survey, performance, training), checking for reliability, validity, factor structure; Model insights to make predictions and track toward these. 

     Present your findings and recommendations to leadership, COEs, HRBPs, and other stakeholders.

     Act as a subject matter expert for questions involving I&D and L&D analytics.

Knowledge, Skills and Abilities:

     Research (Academic and Applied) - Knowledge of how to conduct literature reviews, evaluate research studies, and pull out insights in order to support your own research findings. Strong focus in the I&D and/or L&D space.

     Research Design - Ability to craft well-designed and useful analyses including study design, sampling, hypothesis generation, data collection methods, and implications.

     Statistical Ability - Ability to analyze and interpret research results. Identify relationships and trends in data, as well as any factors that could impact results. Experience with fairness studies (e.g., adverse impact analysis, equity studies).

     Measurement - Knowledge of psychometric best practices for scale development, validation, reliability assessment. Experience with assessment validation as it pertains to bias. Experience with training effectiveness and evaluation. 

     Modeling - Ability to model data over time and use this to make predictions, recommendations, set targets, and track progress. 

     Data Visualization - Ability to display data and results visually, for interpretation ease.

     Presentation and Communication - Ability to present data and results, explain theory, strategy and findings in an easy to understand way to technical and non-technical audiences.

     Qualitative Analysis - Experience with qualitative methods a plus.


Requisite Education and Experience / Minimum Qualifications:

     PhD in Industrial / Organizational Psychology, Quantitative Psychology, Cognitive Psychology or a related quantitative field, or equivalent experience. A focus in I&D or L&D a plus.

     3+ years working in People / HR Analytics within the tech industry in a role in which I&D and/or L&D research and analysis were the focus.

     Highly proficient in crafting and testing research questions and hypotheses across multiple data sources to pull out insights and make actionable, holistic recommendations.  

     Highly proficient in statistics and modeling including: Regression (multiple, logistic, curvilinear, moderation), mean and proportional differences (t-tests, ANOVA, chi-square), measurement and structural models (EFA, CFA, SEM, latent growth), and other modeling / classification methods (e.g., time series modeling, random forests, IRT).  

     Proficient in scale / assessment development including: item analysis, functioning, and reduction (EFA, CFA); reliability analysis; validity assessment. 

     Highly proficient with statistical software (e.g., R, M-Plus, SPSS).

     Proficient in experimental design and analysis. 

     Proficiency in NLP, text mining, and/or other qualitative methods a plus.

     Proficiency with tableau and SQL a plus.


We are committed to an inclusive and diverse Twitter. Twitter is an equal opportunity employer. We do not discriminate based on race, ethnicity, color, ancestry, national origin, religion, sex, sexual orientation, gender identity, age, disability, veteran status, genetic information, marital status or any other legally protected status.

San Francisco Applicants: Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

Engineering Hiring Process

Step 1

Once your application is received, a recruiter will reach out pending your qualifications are a match for the role.

Step 2

If your background is a match, you may have 1-2 technical phone interviews or be given the chance to provide a work sample depending on the role.

Step 3

If the phone interviews go well or your work sample is strong, the final step includes interviews with 5-6 people held onsite in our office.


Personal Information

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U.S.  Equal Employment Opportunity Information  (Completion is Voluntary)

At Twitter, we have a bold aspiration to reach every person on the planet. We believe that goal is more attainable with a team that understands and represents different cultures and backgrounds and we are committed to an inclusive and diverse Twitter.

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Twitter is an equal opportunity employer. We do not discriminate based on race, color, ethnicity, ancestry, national origin, religion, sex, gender, gender identity, gender expression, sexual orientation, age, disability, veteran status, genetic information, marital status or any legally protected status.

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