Analytics & Data Solutions Manager/Team Leader
Job in
Spokane, Spokane County, Washington, 99201, USA
Listing for:
Gesa Credit Union
Full Time
position
Listed on 2026-07-01
Job specializations:
-
IT/Tech
Data Analyst, Data Science Manager, Business Systems & Technology Analysis
Job Description & How to Apply Below
Analytics And Data Solutions Manager/Team Leader
Under the general supervision of the VP of Business Intelligence, the Analytics and Data Solutions Manager/Team Leader will lead enterprise analytics strategy, delivery, and capability development to drive data-informed decision making across Gesa Credit Union. Serving as a senior leader and trusted advisor, the role ensures analytics solutions align with business priorities, meet governance standards, and deliver high-quality, actionable insights. The position will provide leadership to Data Analysts, establish enterprise analytics standards and best practices, and partner with Data Governance and IT to ensure trusted data foundations.
Additionally, the role advances strategic initiatives in analytics, AI, and machine learning to enhance decision-making, manage risk, and improve business performance.
Here you can join a team who is passionate about serving others, has a desire to do good, and shares a deep love of people. You can engage in meaningful work that impacts your community. You can challenge yourself and grow in your career. And, you can rest assured that your wellbeing and prosperity are our priority.
What You Will Be Doing:
Lead and oversee enterprise analytics and data solutions initiatives to support strategic and operational decision-making across the credit unionProvide direct leadership, coaching, and performance management for the Data Analyst teamEstablish clear expectations for analytics delivery that extend beyond dashboard development to include exploratory, diagnostic, and trend‑based analysisGuide and mentor analysts in applying appropriate analytical techniques, including basic statistical analysis where appropriate, to better understand drivers, patterns, and outcomesEnsure analytics deliverables clearly communicate insights, implications, and recommended actions, not just metrics or visualizationsDrive data science initiatives by leveraging artificial intelligence (AI) and machine learning (ML) technologies to predict trends, evaluate risks, and optimize business processes across the organizationPartner with business leaders to identify, prioritize, and deliver analytics solutions that address key organizational challenges and opportunitiesCollaborate with Data Intelligence, Data Engineering, Data Governance, and IT teams to ensure analytics solutions are built on reliable, secure, and governed data assetsTemporarily align analysts from business units under centralized analytics leadership, as needed, to accelerate skill development, consistency, and analytical maturityDefine readiness criteria and standards for transitioning analysts back to business units while preserving enterprise analytics practicesSupport the responsible use of advanced analytics, including statistical and exploratory methods, in alignment with business readiness and regulatory expectationsPromote data literacy and a culture of informed, evidence‑based decision‑making across the organizationRepresent the Data Intelligence organization in cross‑functional initiatives, projects, and committees as assignedAbout You:
Strong leadership and people‑management skills, with the ability to develop and motivate analytics professionalsDemonstrated ability to move analytics teams beyond reporting toward meaningful analysis and insight generationStrong understanding of analytics, business intelligence, and decision-making support practices in regulated environmentsFamiliarity with end-to-end business process mapping and P&L financial models, supporting the translation of analytics into operational and financial insight.Ability to translate complex data and analysis into clear, actionable insights for technical and non‑technical audiencesWorking knowledge of modern analytics and data platforms, including cloud‑based analytics ecosystems and visualization toolsProficiency in data analysis tools (SQL, Python, R), data visualization platforms (Tableau, Power BI), and cloud data solutions (Azure Databricks)Understanding of analytical techniques such as trend analysis, segmentation, and basic statistical methodsStrong business acumen, with the ability to connect…
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