Director Analytics

Accountable for leading the Analytics function through direct, hands-on execution, pragmatic business partnership, and modern AI-driven automation. This role is designed for a grounded, operational leader who acts as a problem-solver and builder rather than a traditional manager or theoretical data scientist. The Director of Analytics will drive analytics strategy, write complex code, streamline legacy reporting, and ensure data directly informs business operations.

Crucially, this leader will treat process automation and modern AI execution (utilizing tools like Claude AI, LLM workflows, and automated pipeline scripts) as a daily force multiplier, eliminating manual operational tax, automating reporting routines, and dramatically accelerating time-to-insight for the business.

• Write (complex) SQL, develop Python scripts, and model data and able to teach others on technical work.
• Actively integrate Claude AI and modern LLM tools into daily analytical workflows to accelerate code development, query optimization, dataset analysis, and report generation.
• Take direct execution ownership of high-priority analytical deliverables, critical data pipelines, and ad-hoc executive requests.

• Identify, design, and implement automated workflows to eliminate manual data gathering, repetitive business processes, and spreadsheet-heavy operations.
• Build robust, end-to-end automated reporting pipelines that reduce manual touchpoints and ensure timely, defect-free deliverable schedules.
• Leverage modern automation capabilities (Python automation scripts, AI-assisted workflows, and platform schedulers) to shift the team away from manual maintenance toward high-value analysis.

• Partner directly with operational leaders and executive stakeholders to define core business problems and deliver practical, decision-ready answers.
• Translate complex data into clear operational language that non-technical leaders can immediately act upon.
• Focus the analytics function on business ROI, operational efficiency, and commercial impact rather than abstract modeling or theoretical data science.
• Communicate status, data realities, and trade-offs to senior leadership with complete transparency.

• Lead and mentor a team of analysts by setting technical standards, conducting code reviews, and working side-by-side with them on major initiatives.
• Train and enable team members on leveraging modern AI tools (such as Claude AI) to amplify individual productivity, debug code faster, and automate their daily routines.
• Shift the team's posture from reactive order-takers into proactive business partners.

• Audit existing reporting environments, retire outdated legacy reports, and replace manual processes with automated self-service dashboards.
• Establish standardized enterprise KPI frameworks, single-source-of-truth definitions, and reconciliation controls to eliminate metric discrepancies across reports.
• Document data logic, automation pipelines, and operational workflows to build institutional knowledge.

• Education & Experience: Bachelor's degree in Analytics, Finance, Operations, Computer Science, or related quantitative field (or equivalent experience) and 7+ years of experience in hands-on data analytics, business intelligence, or process engineering.
• Applied AI & Productivity Tools: Hands-on proficiency using Claude AI and modern LLM platforms to assist in query generation, code debugging (SQL/Python), document/data interpretation, and workflow acceleration.
• Process Automation: Demonstrated experience automating manual business processes and reporting routines using Python, SQL, workflow platforms, or scripting tools.
• Technical Mastery: Deep technical proficiency in relational databases and SQL (complex joins, stored procedures, views, CTEs, and query performance tuning).
• BI & Data Viz: 4+ years of hands-on experience designing, building, and deploying operational dashboards and reports (e.g., Power BI, SSRS, Tableau).
• Programming Skills: Strong working proficiency in Python for data manipulation, process automation, and pipeline construction.
• Active Leadership: Proven experience leading technical team members while remaining actively engaged in technical deliverables.

• 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 directly into business intelligence or operational workflows.
• Track record of consolidating redundant legacy reporting suites into automated, streamlined self-service tools.

• Applied AI & Automation: Leverages tools like Claude AI, LLMs, and scripting as a daily force multiplier to automate processes and accelerate output.
• Business-Grounded Problem Solving: Connects technical output directly to commercial outcomes.
• Hands-On Technical Execution: Maintains active technical skills in SQL, Python, automation scripts, and visualization tools.
• Active Leadership: Teaches, mentors, and upskills team members through direct collaboration and hands-on guidance.
• Prioritization & Speed: Eliminates manual bottlenecks and pushes back on low-impact work.

The ideal candidate is a pragmatic, execution-focused leader who treats AI tools (like Claude AI) and process automation not as buzzwords, but as essential daily levers to get work done faster and smarter. They prefer writing queries, automating workflows, and solving operational puzzles over sitting in administrative management meetings.

Naturally curious and uncomfortable with manual status-quo processes, they do not wait for tickets or requirements to be handed to them. They actively seek out manual business pain points, automate redundant reporting tax, and build cleaner, faster, and more reliable analytics systems.