Director Analytics

Select Portfolio Servicing, Inc.•West Valley City, UT

About The Position

The Director Analytics leads the Analytics function through hands-on execution, practical business partnership, and AI-driven automation. This operational leader drives analytics strategy, writes complex code, modernizes legacy reporting, and ensures data informs business operations. The role uses tools such as Claude AI, LLM workflows, and automated pipeline scripts to reduce manual work, automate reporting, and accelerate time to insight. The Director works directly on high-priority deliverables and data pipelines while partnering with business leaders to deliver practical, decision-ready analysis focused on ROI, operational efficiency, and commercial impact. The Director also leads and mentors analysts through technical standards, code reviews, and collaborative work; enables the team to use AI tools effectively; and modernizes reporting governance through standardized KPIs, reliable definitions, reconciliation controls, documentation, and automated self-service dashboards.

Requirements

Bachelor's degree in Analytics, Finance, Operations, Computer Science, or a related quantitative field, or equivalent experience.
At least 7 years of experience in hands-on data analytics, business intelligence, or process engineering.
Hands-on proficiency with Claude AI and modern LLM platforms for query generation, SQL/Python debugging, document and data interpretation, and workflow acceleration.
Demonstrated experience automating manual business processes and reporting routines using Python, SQL, workflow platforms, or scripting tools.
Deep technical proficiency in relational databases and SQL, including complex joins, stored procedures, views, CTEs, and query performance tuning.
At least 4 years of hands-on experience designing, building, and deploying operational dashboards and reports using tools such as Power BI, SSRS, or Tableau.
Strong working proficiency in Python for data manipulation, process automation, and pipeline construction.
Proven experience leading technical team members while remaining actively engaged in technical deliverables.

Nice To Haves

Master's degree in a quantitative or business discipline.
Experience in mortgage servicing, financial services, lending, or portfolio analytics.
Experience integrating LLM APIs, custom prompts, or automation tools into business intelligence or operational workflows.
Track record of consolidating redundant legacy reporting suites into automated, streamlined self-service tools.

Responsibilities

Write complex SQL, develop Python scripts, model data, and teach others technical work.
Integrate Claude AI and modern LLM tools into analytical workflows to accelerate code development, query optimization, dataset analysis, and report generation.
Own execution of high-priority analytical deliverables, critical data pipelines, and ad hoc executive requests.
Identify, design, and implement automated workflows that eliminate manual data gathering, repetitive business processes, and spreadsheet-heavy operations.
Build end-to-end automated reporting pipelines that reduce manual touchpoints and deliver timely, defect-free reports.
Use Python automation, AI-assisted workflows, and platform schedulers to reduce manual maintenance and enable higher-value analysis.
Partner with operational leaders and executive stakeholders to define business problems and deliver practical, decision-ready answers.
Translate complex data into clear operational language for non-technical leaders.
Focus analytics work on business ROI, operational efficiency, and commercial impact.
Communicate status, data realities, and trade-offs transparently to senior leadership.
Lead and mentor analysts, set technical standards, conduct code reviews, and collaborate on major initiatives.
Train and enable team members to use modern AI tools to improve productivity, debug code, and automate daily routines.
Shift the team from reactive order-taking toward proactive business partnership.
Audit reporting environments, retire outdated reports, and replace manual processes with automated self-service dashboards.
Establish standardized enterprise KPI frameworks, single-source-of-truth definitions, and reconciliation controls.
Document data logic, automation pipelines, and operational workflows.