Data Science (Machine Learning) for Paques

PT. Lintas Teknologi Indonesia; Jakarta Utara; On-site; IDR 400,000,000 - 600,000,000; Full time

Job summary

PT. Lintas Teknologi Indonesia seeks a senior Data Scientist to lead scalable ML initiatives for Paques. You will design, implement, and deploy data science solutions to aid executive decisions and strategic insights.

The role requires 5+ years in data science, strong Python and ML/DL expertise, NLP, time-series forecasting, and hands-on MLOps. Collaboration with AI Architects and Data Engineers is expected.

Qualifications

• Bachelor's degree in Engineering, Computer Science, Mathematics, Statistics, Data Science or related fields.
• Minimum 5+ years of experience in data science, machine learning, predictive analytics or statistical modelling.
• Strong knowledge of ML algorithms, natural language processing, time-series forecasting and statistical analysis.
• Proficiency in Python and data science libraries such as Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch, XGBoost or LightGBM.
• Experience with SQL, large-scale datasets, feature engineering, and data visualization.
• Hands-on experience with MLOps tools and production model deployment.
• Familiarity with Generative AI, LLMs, Retrieval-Augmented Generation (RAG), embeddings and vector databases is highly preferred.
• Strong understanding of AI governance, model evaluation, explainability and responsible AI principles.

Responsibilities

• Design, implement, and optimize scalable data science solutions supporting executive decision-making.
• Develop machine learning models for prediction, classification, anomaly detection, forecasting, sentiment analysis and risk scoring.
• Analyze structured and unstructured datasets to uncover insights and emerging trends.
• Develop statistical models, predictive analytics and AI-driven recommendation systems.
• Build, evaluate, deploy and monitor machine learning models in production environments.
• Collaborate with AI Architects and Data Engineers to integrate machine learning with Generative AI and RAG pipelines.
• Design experiments, evaluation metrics and continuous feedback mechanisms to improve model performance.
• Ensure data science solutions are scalable, maintainable and production-ready.
• Support the development of executive intelligence products through advanced analytics and AI.
• Contribute to the adoption of best practices in machine learning, MLOps and responsible AI.

Skills

Python

Pandas

NumPy

Scikit-learn

TensorFlow

PyTorch

XGBoost/LightGBM

NLP

ML algorithms

MLOps

SQL

Data visualization

Time-series forecasting

Education

Bachelor's degree in Engineering, CS, Mathematics, Statistics, DS or related field

Tools

MLflow

Docker

Kubernetes

Jupyter

Vector databases

Job description

Data Science (Machine Learning) for Paques

Design, implement, and optimize scalable data science solutions supporting executive decision-making. Develop machine learning models for prediction, classification, anomaly detection, forecasting, sentiment analysis and risk scoring. Analyze structured and unstructured datasets to uncover insights and emerging trends.

Key responsibilities

Design, implement, and optimize scalable data science solutions supporting executive decision-making

Develop machine learning models for prediction, classification, anomaly detection, forecasting, sentiment analysis and risk scoring

Analyze structured and unstructured datasets to uncover insights and emerging trends

Develop statistical models, predictive analytics and AI-driven recommendation systems

Build, evaluate, deploy and monitor machine learning models in production environments

Collaborate with AI Architects and Data Engineers to integrate machine learning with Generative AI and RAG pipelines

Design experiments, evaluation metrics and continuous feedback mechanisms to improve model performance

Ensure data science solutions are scalable, maintainable and production-ready

Support the development of executive intelligence products through advanced analytics and AI

Contribute to the adoption of best practices in machine learning, MLOps and responsible AI

About you

Bachelor's degree in Engineering, Computer Science, Mathematics, Statistics, Data Science or related fields

Minimum 5+ years of experience in data science, machine learning, predictive analytics or statistical modelling

Strong knowledge of machine learning algorithms, natural language processing, time-series forecasting and statistical analysis

Proficiency in Python and data science libraries such as Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch, XGBoost or LightGBM

Experience working with SQL, large-scale datasets, feature engineering, and data visualization

Hands-on experience with MLOps tools and production model deployment

Familiarity with Generative AI, LLMs, Retrieval-Augmented Generation (RAG), embeddings and vector databases is highly preferred

Strong understanding of AI governance, model evaluation, explainability and responsible AI principles

Excellent analytical, problem-solving, communication and presentation skills

Telecommunications & Internet Service Providers 101-1,000 employees

Lintas Group was established on August 2001 by the former leadership team of Lucent Indonesia, we have grown from 40 to more than 200 professionals. We have successfully deployed core infrastructure, applications and managed services solutions to major telecommunication operator across the Indonesian archipelago and abroad. We manage projects from the most remote rural locations to city centers, from single item delivery to the implementation of complex network and mission critical software applications.

Lintas Group was established on August 2001 by the former leadership team of Lucent Indonesia, we have grown from 40 to more than 200 professionals. We have successfully deployed core infrastructure, applications and managed services solutions to major telecommunication operator across the Indonesian archipelago and abroad. We manage projects from the most remote rural locations to city centers, from single item delivery to the implementation of complex network and mission critical software applications.