Data Scientist

Smart Communications, Inc.; Philippines; On-site; PHP 1,200,000 - 1,600,000; Full time

Job summary

Smart Communications, Inc. seeks an experienced Machine Learning Engineer to collaborate with data science and engineering teams to build, deploy, and monitor ML models in on-prem and cloud environments.

You will own the full ML lifecycle—from data prep and feature engineering to deployment, monitoring, and responsible AI practices—ensuring scalable, reliable models and clear communication of insights to stakeholders.

Qualifications

• Bachelor's degree in a quantitative discipline.
• 2+ years of experience with the full ML/AI lifecycle from data preparation to deployment and monitoring.
• Strong proficiency in Python and SQL; experience with AWS/Databricks.
• Excellent communication skills to explain ML/AI concepts to stakeholders.
• Exposure to Generative AI or LLMs with understanding of responsible AI practices (bias, data privacy).

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 for training and inference.
• Ensure the scalability, reliability, and performance of machine learning models.
• Monitor and maintain deployed models, implement updates, and troubleshoot issues.
• Assist in designing and maintaining ML 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.

Skills

Python

SQL

AWS/Databricks

Communication

Responsible AI

Generative AI/LLMs

Education

Bachelor's degree in Data Science or related quantitative field

Tools

Git

CI/CD

Job description

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

Nice to Have:

• Hands-on experience with LLMOps, RAG, or Agentic AI
• Version Control (git) and experience with CI/CD pipelines for ML model deployment