Senior ML Engineer: Forecasting, Pipelines & MLOps

PT. Lintas Teknologi Indonesia; Kebayoran Baru; On-site; IDR 400,000,000 - 560,000,000; Full time

Job summary

Lintas Group is seeking a Senior Data Scientist to design, implement, and optimize scalable data pipelines and analytics standards. You will design, build and optimize machine learning models for prediction at fine-grained levels and deploy forecasting models per segment, adapting to changing data patterns.

The role emphasizes producing production-ready, scalable solutions, monitoring model performance, and collaborating with other data scientists to align standards and metrics.

Qualifications

• Bachelor's degree in engineering, computer science, finance, mathematics, or related fields.
• 5+ years of industry experience in data mining, ML, statistical analysis, or predictive modelling.
• Strong experience in ML areas such as NLP, computer vision, time-series and statistical learning theory.
• Proficiency in Python and building multi-model forecasting solutions.

Responsibilities

• Design, implement, and optimize scalable data pipelines and analytics standards.
• Design, build and optimize ML models for prediction at fine-grained levels.
• Select, train, retrain and deploy forecasting models per segment.
• Develop informatics and data science solutions for diverse applications with support.
• Monitor model performance and implement improvements over time.
• Collaborate with data scientists to align modelling standards and metrics.

Skills

Python

Machine Learning

Time-series

NLP

Computer Vision

MLOps

SQL

Education

Bachelor's degree in engineering, computer science, finance, mathematics, or related fields

Tools

TensorFlow

PyTorch

YOLO

OpenCV

SQL

Job description

Lintas Group is seeking a Senior Data Scientist to design, implement, and optimize scalable data pipelines and analytics standards. You will design, build and optimize machine learning models for prediction at fine-grained levels and deploy forecasting models per segment, adapting to changing data patterns.

The role emphasizes producing production-ready, scalable solutions, monitoring model performance, and collaborating with other data scientists to align standards and metrics.