Jr. Data Scientist

Smart Communications, Inc.; Makati; On-site; PHP 1,000,000 - 1,800,000; Full time

Job summary

Smart Communications, Inc. is seeking an experienced ML Engineer to advance the full ML lifecycle from data prep to deployment and monitoring. You will collaborate with data science and engineering teams to build, optimize, and deploy models across on‑premises and cloud environments.

The role requires strong Python/SQL skills and practical experience with AWS/Databricks, plus the ability to communicate complex ML concepts to stakeholders and ensure responsible AI practices are followed.

Qualifications

• Bachelor's degree in a quantitative field such as Data Science, Statistics, Computer Science, or related 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).
• Hands-on experience with LLMOps, RAG, or Agentic AI.
• Version Control (git) and experience with CI/CD pipelines for ML model deployment.

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.

Skills

ML lifecycle experience

Communication skills

Generative AI / LLMs exposure

LLMOps / RAG / Agentic AI

Git / CI-CD for ML

Education

Bachelor's degree in quantitative field

Tools

Python

SQL

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.