Senior Research Data Scientist

Boeing•Seattle, WA

1d•Onsite

About The Position

Boeing's Global Talent, Development and Employee Experience organization has an exciting opportunity for a Senior Research Data Scientist to join the Employee Listening, Organizational Research, and Talent Assessment Team in Seattle, WA. The person in this role will lead deep dive analysis of employee survey, assessment, and workforce data, uncover meaningful organizational insights, and translate complex findings into compelling executive level narratives. This role sits at the intersection of research, analytics, strategy, and storytelling, ideal for someone who thrives on turning data into action and influencing senior leaders with clarity and confidence. You will help set the long-term research roadmap, defining measurement frameworks and success metrics, and establish standards for scientific rigor, reproducibility, practical and responsible use of AI/ML. In this role, you will analyze large and complex datasets from surveys, assessments, HR systems, and business sources to generate actionable insights that inform organizational strategy, talent decisions, and employee experience improvements. You will lead mixed methods research, apply advanced statistical and predictive analytics, and use both structured and unstructured data to identify business trends, drivers, risks, and opportunities. You will partner with executive leaders, HR, talent, and business teams to frame research questions, synthesize findings, and shape decisions through high impact reporting and storytelling. The ideal candidate combines strong technical expertise with the ability to simplify complex information, influence stakeholders, and help leaders understand the “so what” behind the data.

Requirements

Master’s degree or higher in a quantitative field such as Data Science, Statistics, Economics, Operations Research, Machine Learning, Engineering, Industrial Organizational Psychology, Organizational Behavior, Psychometrics, Sociology, or a related discipline
5+ years of experience in data science, quantitative research science, or data analytics
5+ years of experience with the following data analytics methods Machine Learning, Simulation, Statistics, Data Mining, Regression, Survival Analysis, Time series models
5+ years of experience in data analysis algorithms (e.g. data mining, statistics, machine learning, natural language processing, text mining, visual analytics) and building Descriptive, Predictive and Prescriptive models
5+ years of experience in database management, programming, statistical modeling and/or machine learning (SQL, R, Python, JMP, Tableau, etc.)
Experience in Business Intelligence/data analytics tools (Microsoft Power BI, Dashboards, SQL, Tableau, etc.)

Nice To Haves

10+ years of industry experience
Experience with HR systems and employee data environments
Experience applying AI to automate, accelerate, or optimize analytics, research, or reporting workflows
Experience with employee engagement, culture, leadership, talent, or organizational effectiveness research
Experience applying machine learning models from ideation through monitoring and maintenance
Capability to present highly technical information to nontechnical audiences
Capability to influence senior leaders on strategy, trade-offs, and policy decisions using evidence-based recommendations
Experience applying leading AI techniques and libraries to solve complex business problems and deliver measurable results
Strong visualization skills and experience creating compelling charts, dashboards, and executive summaries
Experience teaching, mentoring, and developing others

Responsibilities

Lead advanced analysis of organizational survey, assessment, and workforce data to identify trends, drivers, risks, and opportunities
Design and execute research approaches to answer complex business and organizational questions using survey, assessment, interview, and workforce data
Translate ambiguous data into decision-ready executive syntheses, including recommendations, options, trade-offs, risks, and implementation considerations
Develop high-impact executive reports, presentations, and dashboards that tell a compelling data story
Partner with leaders, HR, talent, and business teams to define research questions and inform strategy
Synthesize multiple data sources, including surveys, assessments, open-ended feedback, internal business outcome metrics, and external benchmarks
Apply advanced statistical analysis, machine learning, and predictive modeling to surface insights and forecast outcomes
Advance NLP methods, including sentiment analysis, topic modeling, and entity recognition, to analyze unstructured text data
Conduct qualitative analysis, including coding, thematic analysis, and content analysis, to derive insights from narrative data
Ensure scientific rigor, validity, and reproducibility across all research and analytics through documented methods, version-controlled code, QA checks, and peer review
Present findings to senior stakeholders with confidence, clarity, and influence
Improve research methodologies, reporting standards, and storytelling approaches
Provide technical leadership, guidance, and mentoring to cross-functional partners and teammates
Identify and implement practical AI use cases that streamline workflows, automate repetitive tasks, improve analytical efficiency, and scale research output
Partner with other scientists to build team capability through coaching, documentation, and examples of effective day-to-day AI use