Jr. Data Scientist

PLDT INC; Makati; On-site; PHP 1,200,000 - 2,400,000; Full time

Job summary

PLDT INC is seeking an experienced ML/AI professional to lead model development and deployment across on-premises and cloud environments. You will manage data preparation, feature engineering, and deployment while ensuring model performance and reliability.

Candidates should have strong Python/SQL skills, familiarity with AWS/Databricks, and a track record in responsible AI practices. Collaboration with cross‑functional teams is essential for success.

Qualifications

• 2–4+ years’ experience with the full ML/AI lifecycle from data preparation to deployment and monitoring.
• Strong proficiency in Python and SQL, plus experience with AWS/Databricks.
• Clear communication to explain ML concepts to diverse stakeholders.
• Exposure to Generative AI/LLMs and responsible AI practices (bias, data privacy).
• Hands‑on ML pipelines: LLMOps, RAG, or Agentic AI experience.
• Version Control (git) and CI/CD pipelines for ML deployment.

Responsibilities

• Collaborate with data science and engineering to develop, optimize, and deploy models on premises and in cloud.
• Oversee the ML lifecycle from data prep to deployment and monitoring.
• Prepare, clean, and transform data for training and inference.
• Ensure scalability, reliability, and performance of ML models.
• Monitor deployed models, implement updates, and troubleshoot issues.
• Design and maintain ML pipelines for efficient data flow and deployment.
• Translate analytical findings into actionable recommendations.
• Ensure responsible AI practices addressing bias, fairness, and data privacy.

Skills

ML lifecycle experience

Python

SQL

Generative AI/LLMs

LLMOps / RAG / Agentic AI

Git version control

CI/CD for ML

Education

Bachelor’s degree in quantitative field

Tools

AWS

Databricks

Job description

Education

Bachelor’s degree holder of any quantitative discipline such as Data Science, Statistics, Computer Science, or related quantitative field

Qualifications

• 2–4+ years’ experience with the full ML/AI lifecycle from data preparation to deployment and monitoring
• Strong proficiency in Python, SQL, and experience with AWS/Databricks environments
• Good communication skills to explain complex ML/AI concepts to diverse stakeholders
• Exposure to Generative AI or LLMs, with understanding of responsible AI practices (bias, fairness, data privacy)
• Hands‑on experience with LLMOps, RAG, or Agentic AI
• Version Control (git) and experience with CI/CD pipelines for ML model deployment

Duties and Responsibilities

• Collaborate with data science and engineering teams to develop, optimize, and deploy machine learning models in on premises and cloud environments.
• Oversee the ML model lifecycle from data preparation and feature engineering to deployment and monitoring.
• Prepare, clean, and transform data to be used for training and inference.
• Ensure the scalability, reliability, and performance of machine learning models.
• Monitor and maintain deployed models, implement updates, and troubleshoot any issues that may arise.
• Assist in designing and maintaining machine learning pipelines, ensuring efficient data flow and model deployment.
• Translate analytical findings into clear recommendations for stakeholders.
• Ensure responsible AI practices are followed, addressing bias, fairness, and ethical considerations in line with Data Privacy, Cybersecurity, and AI policies.