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At Boeing, we innovate and collaborate to make the world a better place. We’re committed to fostering an environment for every teammate that’s welcoming, respectful and inclusive, with great opportunity for professional growth. Find your future with us. Boeing Enterprise AI and Data (a part of Information Digital Technology & Security) is seeking a Senior/Lead Data Scientist to join a Data Science and Analytics team in the St. Louis, MO area to support enterprise business-critical outcomes across areas such as Manufacturing, Supply Chain Management and Aftermarket product support. This role will lead the development and deployment of high-impact predictive and prescriptive analytics and will shape analytics strategy, architecture, and technical direction across a portfolio of complex problems. The ideal candidate brings deep expertise in advanced analytics and machine learning, strong engineering and MLOps instincts, and the ability to influence senior stakeholders and cross-functional teams to deliver measurable business results.
Job Responsibility:
Leads the design, development, validation, deployment, and lifecycle management of end-to-end predictive/prescriptive analytics solutions (e.g., forecasting, anomaly detection, optimization, risk scoring, early-warning systems)
Owns problem framing with business and operational stakeholders
translates ambiguous needs into measurable objectives, success metrics, analytical requirements, and delivery roadmaps
Selects best-fit methodologies (e.g., statistical modeling, machine learning, deep learning, NLP, computer vision, time series, simulation, optimization) and defines modeling approaches, evaluation strategies, and governance
Drives data preparation and feature engineering for complex, multi-source datasets
establishes repeatable pipelines for data quality, lineage, and model inputs
Establishes and enforces modeling and engineering standards (code quality, peer review, documentation, reproducibility, bias/robustness checks, monitoring, retraining triggers)
Leads technical reviews (design, algorithm, code, and model risk reviews) and provides guidance to other data scientists and partner teams
Partners cross-functionally with analytics, engineering, quality, safety, operations, and product/IT teams to integrate solutions into business workflows and decision systems
Influences analytics strategy for the organization, including platform/tooling recommendations, model deployment patterns, experimentation/measurement approaches, and reuse of common assets
Monitors deployed solutions (performance drift, data drift, operational KPIs) and drives continuous improvement through iteration, retraining, and user feedback
Mentors and develops junior data scientists
actively contributes to knowledge sharing, technical communities, and capability building across the organization
Communicates complex technical outcomes clearly to senior leadership, including tradeoffs, risks, assumptions, and expected business impact
Requirements:
Bachelor's degree or higher from an accredited course of study in data science, computer science, machine learning, applied statistics, mathematics, engineering, or related field
10+ years of Data Science experience
10+ years of end-to-end analytics/ML solutions, including problem definition, data preparation, model development, validation, deployment, and monitoring
10+ years experience in a position that requires analytical, quantitative reasoning and/or mathematical modeling skills
10+ years of experience with Python and SQL
10+ years of experience with machine learning/statistical modeling (e.g., regression, classification, clustering, time-series, anomaly detection, causal/experimental methods), including model evaluation and validation
10+ years of experience with data visualization and decision support (e.g., Python, Tableau, Power BI, or equivalent) to communicate insights and drive adoption
5+ years of experience working with cloud and/or enterprise analytics stacks and building production-ready solutions (e.g., Azure/AWS/GCP
Spark/Databricks
containerization and CI/CD patterns)
5+ years of leading technical work and mentoring other data scientists
demonstrated influence across cross-functional stakeholders
ability to communicate technical content in oral and written form
US Secret clearance or ability to obtain one
Nice to have:
Experience supporting manufacturing, quality, safety, or supply chain analytics in an industrial environment
Experience developing and deploying solutions using MLOps/DataOps practices (e.g., Git-based workflows, model registries, automated testing, monitoring, reproducible pipelines)
Experience with NLP/LLMs, computer vision, and/or graph methods applied to operational and engineering data
Experience with optimization and simulation for prescriptive analytics and operational decision support
Experience working with GPUs and computation clusters
Strong track record of presenting technical recommendations and business cases to senior leadership
What we offer:
competitive base pay and variable compensation opportunities
health insurance
flexible spending accounts
health savings accounts
retirement savings plans
life and disability insurance programs
paid and unpaid time away from work
generous company match to your 401(k)
industry-leading tuition assistance program pays your institution directly
fertility, adoption, and surrogacy benefits
up to $10,000 gift match when you support your favorite nonprofit organizations