Senior Data Scientist

Paques Indonesia; Jakarta Pusat; On-site; IDR 350,000,000 - 550,000,000; Full time

Job summary

Paques Indonesia is seeking an experienced Senior Data Scientist to design, implement, and optimize scalable data science solutions that support executive decision-making. You will develop advanced ML models for forecasting, anomaly detection, and risk scoring, collaborate with AI architects, and deploy production-grade models with robust MLOps practices.

The role requires a strong technical background, 5+ years of experience, and excellence in communication and problem solving to translate data

Qualifications

• Bachelor's degree in Engineering, Computer Science, Mathematics, Statistics, Data Science, or related field.
• Minimum 5+ years of experience in data science, ML, predictive analytics, or statistical modelling.
• Strong knowledge of ML algorithms, NLP, 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.
• Strong understanding of AI governance, model evaluation, explainability and responsible AI.

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

Machine learning

NLP

Time-series forecasting

Statistical analysis

Python

Data visualization

Communication skills

Problem-solving

Education

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

Tools

Python

Pandas

NumPy

Scikit-learn

TensorFlow

PyTorch

XGBoost

LightGBM

SQL

Job description

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

Requirements

• 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