Data Scientist

MSBU Konsultan; Sumbawa Besar; Hybrid; IDR 360,000,000 - 600,000,000; Full time

Job summary

MSBU Konsultan seeks an experienced data scientist with 3–5 years in data science or ML focused on mining/industrial data. You will develop predictive models, work with Python/SQL, and implement MLops practices across the lifecycle to deliver insights for operations.

You will also build dashboards and communicate model results to stakeholders, requiring strong technical writing in English and willingness to travel to remote mine sites.

Qualifications

• Bachelor’s degree in Data Science, Statistics, CS, Mining/Geological/Metallurgical Eng., Math, Physics or related quantitative field.
• 3–5 years in data science/ML with mining/industrial data exposure preferred.
• Strong Python (pandas, scikit-learn, PyTorch/TensorFlow) and SQL; Snowpark/Snowflake experience.
• Experience with MLops lifecycle: experiment tracking, feature stores, model monitoring.
• Knowledge of mining data types and ability to build dashboards/analytical apps.

Skills

Analytical thinking

English communication

Python programming

SQL

Dashboard storytelling

Education

Bachelor’s degree in quantitative field

Master’s degree preferred

Tools

Snowpark

Snowflake

MLflow

Streamlit

Power BI

Job description

• Bachelor's degree (S1) in Data Science, Statistics, Computer Science, Mining/Geological/Metallurgical Engineering, Mathematics, Physics, or related quantitative field; Master's degree (S2) is an advantage.
• Minimum 3-5 years of professional experience in data science/machine learning, with at least 1–2 years of exposure to mining, resources, or heavy-industry operational data (production, maintenance, geology, or process data) preferred.
• Good English proficiency (spoken and written) for technical documentation and cross-site/corporate communication;
• Strong analytical rigor, curiosity, and ability to translate ambiguous operational problems into well-scoped data science projects.
• Strong proficiency in Python (pandas, scikit-learn, PyTorch/TensorFlow) and SQL; hands-on experience with Snowpark and Snowflake for model development.
• Practical experience with the MLOps lifecycle: experiment tracking and model registry (MLflow or equivalent), feature stores, and model monitoring/drift detection.
• Working knowledge of statistical and ML techniques relevant to mining: time-series forecasting, classification/regression for predictive maintenance, geostatistics/spatial analysis, and optimization methods.
• Familiarity with mining operational data types (drillhole/assay data, block models, SCADA/IoT sensor streams, fleet management system data) is a strong advantage.
• Experience building dashboards/analytical apps (Streamlit, Power BI, or Snowflake Notebooks) to communicate model outputs to operational stakeholders.
• Understanding of data governance and access-control principles when handling sensitive geological, production, or safety data.
• Relevant certifications is a plus
• Willingness and ability to travel periodically to remote mine-site locations for data validation and stakeholder engagement.