Senior/Lead Data Scientist

Senior/Lead Data Scientist

Company:

The Boeing Company

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.

Position Responsibilities

• 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.

Basic Qualifications (Required Skills/Experience)

• 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 solu