Job Description

Director of Data Analytics and AI

Department: I.T. (Information Technology)

Employment Type: Full Time

Location: Cebu, PH

Compensation: ₱150,000 - ₱200,000 / month

A dynamic, forward-thinking, and results-driven individual to lead our artificial intelligence, machine learning, and enterprise analytics strategy, execution, and team development. Reporting to the VP of IT, this role will define the direction of AI/ML and analytics initiatives, ensuring the development of scalable, high‑performance solutions that drive innovation, operational intelligence, and measurable business value. The ideal candidate will have a strong technical background, experience leading AI/ML and analytics teams, and the ability to align data and AI strategies with organizational objectives.

Key Responsibilities

• Strong expertise in ML algorithms, frameworks (TensorFlow, PyTorch, Scikit-learn), and modern data processing tools.
• Expertise in designing data models, semantic layers, and enterprise datasets for analytics consumption.
• Excellent communication skills with the ability to present complex technical concepts to both technical and non-technical audiences.
• Strong problem-solving and strategic-thinking skills with the ability to drive complex technical initiatives.
• Knowledge of ethical AI principles and data privacy regulations.
• Advanced proficiency in Python, Java, C/C++, Spark, R, Kafka, C#, MATLAB, and modern data communication formats.
• Experience with microservices, Docker, Kubernetes, and cloud platforms (AWS, Azure, GCP).
• Expertise with GraphDB, SQL/NoSQL databases, and general database architecture.
• Experience with industrial automation or power system design is a plus.
• Published research or open-source AI/ML contributions preferred.
• Familiarity with energy industry standards and documentation processes.

Skills, Knowledge & Expertise

• Degree in Computer Science, Engineering, Mathematics, or a related field.
• 10+ years of experience in AI/ML, including supervised/unsupervised learning, reinforcement learning, and LLM-based solutions.
• Proven experience developing, deploying, and scaling ML models and analytics systems in production environments.
• Experience leading multidisciplinary, high-performing data and AI teams.
• Hands-on experience with Power BI, DAX, Power Query, data modeling, and enterprise reporting best practices.
• Experience with Microsoft Fabric (Data Engineering, Data Factory, Lakehouse, Warehouse, Real-Time Analytics).