Manager II | Analytics Enablement Lead

At Popular, we offer a wide variety of services and financial solutions to serve our communities in Puerto Rico, United States & Virgin Islands. As employees, we are dedicated to making our customers dreams come true by offering financial solutions in each stage of their life. Our extensive trajectory demonstrates the resiliency and determination of our employees to innovate, reach for the right solutions and strongly support the communities we serve; this is why we value their diverse skills, experiences and backgrounds.

 

Are you ready for a rewarding career?

Over 8,000 people in Puerto Rico, United States and Virgin Islands work at Popular.

Come and join our community!

The Opportunity

Analytics Enablement Lead plays a critical role in the Analytical Engineering & Enablement function, leading the efforts to enable analytical and machine learning capabilities across the organization. This role requires strong technical acumen combined with leadership and strategic planning skills to facilitate the implementation of analytics and machine learning solutions that drive data-driven decision-making and business innovation. The Analytical/ML Enablement Lead - IV is responsible for guiding a team of specialists, ensuring alignment with organizational goals, and fostering a culture of continuous learning and innovation.

Your key responsibilities:

You will collaborate with multifaceted teams of specialists spread across various locations to offer a broad spectrum of data and analytics solutions. You will address complicated challenges and propel advancement within the Enterprise Data & Analytics function.

Specifically:

• Develop and execute the strategy for analytical and machine learning capabilities, including the identification, evaluation, and adoption of emerging technologies and methodologies.
• Lead a team of Analytical/ML Enablement Specialists, providing mentorship, technical guidance, and career development opportunities.
• Collaborate with business units and cross-functional teams to identify opportunities for applying analytics and machine learning to solve complex business problems.
• Oversee the design and implementation of analytics and machine learning solutions, ensuring compliance with data governance, privacy, and security policies.
• Establish and monitor metrics to evaluate the effectiveness and impact of analytical and machine learning solutions on business performance.
• Foster an environment that encourages innovation, knowledge sharing, and adoption of best practices in analytics and machine learning.
• Liaise with Data Governance and Data Integration teams to ensure that analytical data sources are reliable, secure, and of high quality.
• Develop and maintain documentation and training materials for analytics and machine learning tools and methodologies.
• Manage relationships with external vendors and partners, ensuring alignment with organizational objectives and compliance with contractual obligations.
• Promote data literacy and analytical thinking across the organization through workshops, training sessions, and communications.
• Lead upkeep and optimization of Python and R libraries to support our machine learning initiatives.
• Design both online and offline feature stores, providing efficient data access for machine learning models.
• Spearhead the design of a cutting-edge AI/ML model development environment, facilitating the creation and testing of innovative machine learning models.
• Architect an advanced AI/ML model deployment environment, ensuring seamless and scalable model deployment.
• Coordinate constructing DevOps and DevSecOps pipelines to automate and streamline the machine learning model development and deployment processes.
• Oversee the end-to-end release management process, ensuring the efficient deployment of machine learning models into our production environment.
• Communicate offering of L2 and L3 support for machine learning systems, resolving complex issues, ensuring optimal system performance.
• Supervise a critical role in providing knowledge transfer (KT) to the production support team, ensuring they are well-equipped to maintain and troubleshoot machine learning solutions effectively.
• Define and implement KPIs for platform performance, stability, scalability, cost; additionally, monitor the KPIs and create, publish, and optimize reports.
• Direct and supervising creation, elaboration, estimation, and prioritization of user stories.
• Define and communicate best practices, standards, and guardrails for leveraging analytical platform.
• Lead the design and management of container platforms to enable the containerization and scaling of machine learning applications.
• Collaborate with data, enterprise, cloud, and s