Data Scientist (Nusa Tenggara Barat)

• 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

Skills: Redis, Statistics, Natural Language Processing (NLP), Data Modeling, MongoDB, Deep Learning, Artificial Intelligence, Microsoft SQL Server, Python, Machine Learning