Sr. Director, Enterprise Applications & Data Science (AI)

GIA (Gemological Institute of America)•Carlsbad, CA

6d•$210,000 - $260,000•Onsite

About The Position

The Sr. Director, Enterprise Applications & Data Science (AI) is GIA’s enterprise leader for agentic transformation, accountable for turning data and AI into measurable improvements in speed, accuracy, and cost across the Institute. The role owns the platforms, data, and models supporting core operations: Workday for HCM, Financials, ERP, payroll, and customer invoicing, and the Snowflake, Power BI, and AWS AI ecosystem for enterprise analytics and machine learning. Reporting to the SVP, Chief Information & Transformation Officer, the role sets enterprise applications, data, and AI strategy and leads the Director, Business Systems and the Sr. Manager, Data Science & Analytics. The role advances GIA from batch reporting and AI pilots to real-time analytics, production machine learning—including computer vision for laboratory grading—and AI agents that automate corporate and business processes worldwide. It partners with business leaders to redesign processes, establish governed AI and data practices, build and develop teams, manage strategic vendors and budgets, and deliver measurable operational gains in support of GIA’s mission to ensure public trust in gems and jewelry. This position is located at GIA’s corporate headquarters in Carlsbad, California. Domestic and international travel may be needed, including to GIA Services in India and laboratory locations. Periodic early-morning or evening meetings are required to overlap with GIA Services (India).

Requirements

Bachelor’s degree in computer science, data science, statistics, engineering, or a related quantitative field.
15+ years of progressive experience across enterprise applications, data, and analytics, including 10+ years leading managers and multidisciplinary teams.
Proven record of building and scaling high-performing data science and analytics teams.
Experience leading Workday HCM, Financials, Adaptive Planning, and Learning, with a strong understanding of end-to-end finance processes.
Experience with Snowflake, building data lakes and data warehouses, and automating reporting in Power BI.
Experience delivering real-time analytics and streaming data pipelines at enterprise scale.
Hands-on background in traditional machine learning and AI, including computer vision, decision trees, and random forests.
Expert knowledge of end-to-end finance and HR processes and ability to build credible business cases for an applications, data, and AI portfolio.
Ability to set a multi-year strategy and translate a transformation agenda into a sequenced roadmap with measurable outcomes.
Knowledge of where agents, LLMs, and traditional machine learning create value or risk, and ability to move AI from experimentation to governed production at scale.
Ability to deliver complex, multi-year programs on time and on budget and hold teams accountable for measurable outcomes.
Ability to make sound, timely decisions in a complex, global, multi-system environment, weighing value, cost, risk, and controls with a high degree of autonomy.
Ability to build and retain high-performing technical teams, develop leaders, and plan succession across the US and India.
Ability to lead enterprise-wide adoption of new processes and tools and influence senior executives and business leaders without direct authority.
Ability to explain complex technical topics in plain business terms.
Willingness to travel domestically and internationally as needed, including to GIA Services (India) and laboratory locations.
Availability for periodic early-morning or evening meetings to overlap with GIA Services (India).

Nice To Haves

Master’s degree in Data Science or MBA.
Experience building AI agents and AI automation, including automated reporting with Claude or comparable LLM platforms.
Experience with the AWS AI ecosystem, including SageMaker and Bedrock.

Responsibilities

Set enterprise applications, data, and AI strategy and maintain a rolling 2–3-year roadmap aligned with the CITO’s transformation agenda.
Lead GIA’s agentic transformation, defining how AI agents execute and orchestrate corporate and business processes across Workday, Snowflake, AWS, and Microsoft 365.
Define the reference architecture for agent development, including Claude, Amazon Bedrock, tool integrations, and human-in-the-loop controls, in partnership with the CISO and Enterprise Architecture.
Partner with Finance, Payroll, HR, Laboratory, Education, and Operations leaders to redesign and automate order-to-cash, record-to-report, procure-to-pay, hire-to-retire, laboratory, and customer operations processes.
Build and prioritize the agent and automation portfolio against business cases and own the benefits ledger, including hours returned, cycle time, error rates, and cost avoided.
Drive adoption and change management so automated processes and AI tools become standard practice.
Own Workday as GIA’s system of record for HCM, Financials, Adaptive Planning, Learning, and ERP, including roadmap, tenant management, business process configuration, integrations, and support.
Establish Workday as the source for customer invoicing and the system of record for accounts receivable; lead process design, data migration, integrations, and cutover with Finance.
Deliver multi-country payroll through Workday HCM integration with ADP, including data accuracy and pay-cycle controls.
Partner with Finance on Adaptive Planning and HR on Workday Learning; integrate travel and expense platforms with Workday.
Manage Workday’s two annual feature releases and deploy native Workday AI and agent capabilities alongside custom agents.
Own reporting and integrations, including data flows between Workday, Snowflake, ADP, and laboratory and business systems.
Build GIA’s modern data platform on Snowflake and AWS, including a data lake and enterprise data warehouse, as the trusted source for enterprise reporting.
Move GIA from scheduled batch reports to real-time pipelines and live dashboards for Laboratory, Education, Finance, and Operations.
Automate enterprise reporting in Power BI and shift toward Claude-driven conversational and agentic analytics that retire manual report production.
Direct production machine learning and AI, including computer vision for laboratory grading and supervised models on AWS SageMaker and Bedrock.
Establish MLOps standards for model versioning, monitoring, drift detection, and retraining across production models.
Lead the Director, Business Systems and Sr. Manager, Data Science & Analytics, and build a high-performing applications, data, and AI organization.
Recruit and develop talent in data engineering, data science, ML engineering, agent development, and Workday, including delivery capacity in GIA Services (India).
Set team objectives, manage performance, build career paths, and foster a culture of experimentation and accountability.
Manage strategic partners and vendors, including Workday, Snowflake, Dell Boomi, and implementation partners.
Operationalize AI governance for models and agents, including responsible AI, guardrails, and model risk, with the AI Task Force and CISO.
Maintain IT General Controls, role-based security, and segregation of duties across Workday and financial systems, keeping them audit ready.
Establish data governance, data quality, lineage, and master data standards, and partner with Data Privacy to protect personal and customer data.
Manage the enterprise applications, data, and AI budget, including licenses and partner spend.