Senior/lead Data Scientist

Boeing Boeing · Aerospace · St. Louis City, MO +1

Boeing is seeking a Senior/Lead Data Scientist to join their Enterprise AI and Data team. The role focuses on leading the development and deployment of predictive and prescriptive analytics solutions for manufacturing, supply chain, and aftermarket product support. Responsibilities include problem framing, methodology selection, data preparation, establishing standards, technical reviews, cross-functional partnerships, influencing strategy, monitoring deployed solutions, and mentoring junior scientists. Requires extensive experience in data science, ML, MLOps, cloud environments, and Python/SQL, with a Bachelor's degree and 10+ years of experience.

What you'd actually do

  1. 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).
  2. Owns problem framing with business and operational stakeholders; translates ambiguous needs into measurable objectives, success metrics, analytical requirements, and delivery roadmaps.
  3. 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.
  4. Drives data preparation and feature engineering for complex, multi-source datasets; establishes repeatable pipelines for data quality, lineage, and model inputs.
  5. Establishes and enforces modeling and engineering standards (code quality, peer review, documentation, reproducibility, bias/robustness checks, monitoring, retraining triggers).

Skills

Required

  • Python
  • SQL
  • Machine learning/statistical modeling (regression, classification, clustering, time-series, anomaly detection, causal/experimental methods)
  • Model evaluation and validation
  • Data visualization
  • Cloud and/or enterprise analytics stacks
  • Production-ready solutions
  • Containerization
  • CI/CD patterns
  • Leadership
  • Mentoring
  • Cross-functional stakeholder management
  • Technical communication

Nice to have

  • Manufacturing analytics
  • Quality analytics
  • Safety analytics
  • Supply chain analytics
  • Industrial environment experience
  • MLOps/DataOps practices
  • NLP/LLMs
  • Computer vision
  • Graph methods
  • Optimization
  • Simulation
  • Prescriptive analytics
  • Operational decision support
  • GPUs
  • Computation clusters

What the JD emphasized

  • 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 of 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.

Other signals

  • lead the development and deployment of high-impact predictive and prescriptive analytics
  • shape analytics strategy, architecture, and technical direction
  • deep expertise in advanced analytics and machine learning
  • strong engineering and MLOps instincts
  • influence senior stakeholders and cross-functional teams to deliver measurable business results