Senior Research Data Scientist

## Senior Research Data Scientist — Seattle, WA

Boeing's Global Talent, Development and Employee Experience organization is hiring a Senior Research Data Scientist to join the Employee Listening, Organizational Research, and Talent Assessment Team in Seattle, WA. This person 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. The role sits at the intersection of research, analytics, strategy, and storytelling and is 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, and 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.

The work includes leading mixed methods research, applying advanced statistical and predictive analytics, and using 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 and help leaders understand the “so what” behind the data.

### What you will do and the skills you must bring

• Lead advanced analysis of organizational survey, assessment, and workforce data to identify trends, drivers, risks, and opportunities.

• Design and execute research approaches using survey, assessment, interview, and workforce data and translate ambiguous data into decision-ready executive syntheses with recommendations, options, trade-offs, risks, and implementation considerations.

• Develop high-impact executive reports, presentations, and dashboards that tell a compelling data story and present findings to senior stakeholders with confidence, clarity, and influence.

• 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 through documented methods, version-controlled code, QA checks, and peer review; 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.

### Required background (exact qualifications preserved)

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.).

Preferred: 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 and influence senior leaders; experience applying leading AI techniques and libraries; strong visualization skills; experience teaching, mentoring, and developing others.

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