Senior Manager, Data and Analytics
Everett, WA, US
- Pay
- Pay not listed
- Work setting
On-site stated · location limits — work setting source
Location: Everett, WA (3 days in office) The Manager, Data and Analytics leads the data and analytics team within the CIO organization, with accountability for delivering trusted data products, reporting, and AI models that inform measurable business decisions. This role manages the analytics and AI modeling backlog, the datasets and pipelines those products depend on, and the day-to-day delivery practices of a team of analysts, data scientists, and data engineers. The manager partners closely with business stakeholders and with platform and engineering teams to translate business questions into analytics and modeling work, and to ensure models are validated, monitored, and used responsibly in line with enterprise governance.
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Full-time — employment source
Employment type in the employer’s listing: FULL_TIME
From the employer’s posting
What you’ll work on
Full postingLead, hire and coach a team of analysts, data scientists and data engineers
Deliver AI models for forecasting, propensity, risk and anomaly detection
Build and maintain trusted datasets, pipelines and metric definitions
Manage intake and prioritization of analytics and modeling requests
Monitor deployed models for accuracy, drift and business impact
From the employer’s posting
Lead a team of data analysts, data scientists, and data engineers, including hiring, coaching, performance management, and capability development.
Deliver business productivity via AI models forecasting, propensity, risk, demand, and anomaly detection from problem framing through validation, deployment, and ongoing monitoring.
Build and maintain trusted datasets, pipelines, and metric definitions that support reporting, self-service analytics, and model features.
Manage intake and prioritization of analytics and modeling requests, including feasibility assessment, effort sizing, and expected business benefit.
Monitor deployed models for accuracy, drift, and business impact, and retrain or retire models as conditions change.
Education & alternatives
Role Characteristics People-management role with direct accountability for the delivery of analytics and AI modeling work, the capability of the team, and the quality of the data products the team owns. Balances fast, exploratory analysis with the rigor required for production models and trusted reporting. Qualifications and Experience • 5+ years of experience in data analytics, data science, or AI modeling, including leading or managing a team. • Hands-on depth in statistical and machine learning methods for prediction (regression, classification, time-series forecasting, clustering) and in evaluating model performance. • Strong SQL plus Python or R, with working experience in modern data warehouse and pipeline tooling. • Demonstrated experience taking AI models into production and monitoring them for accuracy, drift, and business impact. • Experience with BI and visualization tools and building decision-ready reporting for business audiences. • Proven ability to scope ambiguous business questions into deliverable analytical work and to communicate results to non-technical stakeholders. • Working knowledge of data governance, privacy, and responsible AI expectations as applied to data access and model development. • Bachelor's degree in a quantitative field, or equivalent practical experience. Success Measures
Tools in this posting
- Python
- R
- SQL
Source — Tool mentions in context
Role Characteristics People-management role with direct accountability for the delivery of analytics and AI modeling work, the capability of the team, and the quality of the data products the team owns. Balances fast, exploratory analysis with the rigor required for production models and trusted reporting. Qualifications and Experience • 5+ years of experience in data analytics, data science, or AI modeling, including leading or managing a team. • Hands-on depth in statistical and machine learning methods for prediction (regression, classification, time-series forecasting, clustering) and in evaluating model performance. • Strong SQL plus Python or R, with working experience in modern data warehouse and pipeline tooling. • Demonstrated experience taking AI models into production and monitoring them for accuracy, drift, and business impact. • Experience with BI and visualization tools and building decision-ready reporting for business audiences. • Proven ability to scope ambiguous business questions into deliverable analytical work and to communicate results to non-technical stakeholders. • Working knowledge of data governance, privacy, and responsible AI expectations as applied to data access and model development. • Bachelor's degree in a quantitative field, or equivalent practical experience. Success Measures
About Fortive
Fluke is leading the world in creating software, test tools and technology that will support customers today and in the future.
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- Sep 9, 2026 · 44 days ago
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- Last seen by us
- Oct 23, 2026
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Everett, WA, US
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