Senior/Lead Data Scientist

Boeing

. 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).

Posted 5/15/2026full-timeSt. Louis • Montana • 🇺🇸 United StatesSenior💰 $216,000 - $250,000 per yearWebsite

Tech Stack

Tools & technologies

AWSAzureCloudGoogle Cloud PlatformPythonSparkSQLTableau

About the role

Key responsibilities & impact

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

What you’ll need

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.

Benefits

Comp & perks

Health insurance
Flexible spending accounts
Health savings accounts
Retirement savings plans
Life and disability insurance programs
Paid time off

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

data sciencemachine learningstatistical modelingdata preparationfeature engineeringmodel developmentmodel validationdata visualizationquantitative reasoningmathematical modeling

Soft Skills

problem framingcommunicationmentoringinfluencingcross-functional collaborationtechnical guidanceknowledge sharingcontinuous improvementanalytical thinkingleadership

Certifications

Bachelor's degreeUS Secret clearance