People Research Scientist, Leadership
Compensation: $103,330.00 - $127,920.00 /year *
Employment Type: Full-Time
Industry: Scientific Research
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Facebooks mission is to give people the power to build community and bring the world closer together. Through our family of apps and services, were building a different kind of company that connects billions of people around the world, gives them ways to share what matters most to them, and helps bring people closer together. Whether were creating new products or helping a small business expand its reach, people at Facebook are builders at heart. Our global teams are constantly iterating, solving problems, and working together to empower people around the world to build community and connect in meaningful ways. Together, we can help people build stronger communities were just getting started.At Facebook, we pride ourselves on making data-informed decisions. This includes not only decisions we make about our platform, which serves over 2 billion users, but also how we learn more about our most valuable asset our people. For instance, we use data to understand how to hire top talent, to ensure our people are engaged, and to support diversity. We re looking for an experienced People Research Scientist or Data Scientist to join our People Analytics function. Our team uncovers data-driven insights to better attract, develop, motivate, and retain Facebook s most important asset our people. This role will serve as an active partner with Learning & Development and Business Leaders to perform research and analyses to establish meaningful methods and measurements to assess, identify, develop and select a diverse pool of leadership talent. The person we are seeking will be passionate about creating the new and the different, implementing innovative approaches to how we develop talent and building the next generation of organizational capabilities. This is an excellent opportunity for a Data Scientist interested in the application of AI methodologies in the domain of Management Science and Leadership, an area with ample whitespace for impact.RESPONSIBILITIESApply your expertise in people research, quantitative analysis, data science and data visualization to provide insights on talent management and leadership development initiatives, including talent reviews, manager effectiveness, succession planning, talent pipeline, and leadership learning and development programs.Help shape the strategy for leadership development through metrics and analytics that quantify progress and identify gaps.Build robust partnerships with the Learning & Development organization and Business Leaders to reinforce key programs which have already been designed while continuing to improve and enhance these programs to support ongoing initiatives.Collaborate with data engineering and visualization engineers to access and manipulate data, explain data gathering requirements, and visualize results.Bring together Facebook-specific data and outside research to inform the design of programs and drive change for the better.Maintain knowledge of the latest developments in Learning and Development, as well as new tools and technology to offer guidance for continuous improvement.Communicate statistical analyses and results, along with implications, to technical and non-technical audiences.Collaborate effectively with other team members.Demonstrate exceptional judgment and discretion when dealing with highly sensitive people data.MINIMUM QUALIFICATIONSPhD with 5+ years of experience, or MS with 8+ years of experience in a field emphasizing quantitative analysis (e.g., Computer Science, Statistics, Math, Industrial/Organizational Psychology, Organizational Behavior, Labor Economics, Management, Policy Analysis, Human Computer Interaction etc.).3+ years of experience conducting quantitative research in an organization or consulting environment, including working with stakeholders to understand and clarify their research needs, and communicating analyses to technical and non-technical audiences.Experience analyzing structured and unstructured data using languages such as SQL, R or Python.Knowledge of algorithms for data mining, machine learning, and natural language processing (NLP).Experience with an area of People Research (e.g. compensation, benefits, employee engagement, performance management, diversity and inclusion, learning and development, leadership etc.) in organizations.Experience communicating technical results to technical and non-technical audiences.PREFERRED QUALIFICATIONS3+ years of experience with machine learning, text mining/natural language processing or modeling high-dimensional data.3+ years of experience applying multivariate statistical methods such as GLM, analysis of quasi-experimental research designs with non-equivalent groups (e.g. regression adjustment, matching, propensity score stratification), longitudinal analysis, classification, dimension reduction, clustering, hierarchical linear (random effects) modeling, etc. to people research problems in organizations.5+ years of experience working internally (as opposed to consulting) in an organization with 500+ professional employees (e.g., high-tech, financial services, healthcare, biotech, etc.).Experience conducting research on leadership effectiveness or employee learning and development.Experience architecting and automating data and analytics solutions that can provide insights and recommendations at scale.Possess the experience, maturity, presence and judgment to gain credibility and respect with business leaders and experience dealing with senior leadership teams in large organizations.Experience conceiving, developing, running pilot tests, implementing, and continuously improving large-scale people processes.Experienced in survey design.Expertise in consumable data visualization techniques that allows an audience to quickly grasp insights.Comfortable with ambiguity and changing requirements.
Associated topics: business, business analyst, commercial, commission, estate, financial analyst, investment, pricing, real estate, valuation
* The salary listed in the header is an estimate based on salary data for similar jobs in the same area. Salary or compensation data found in the job description is accurate.
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