Data Scientist

Job Overview: We are seeking a Data Scientist to drive data-driven decision-making and develop innovative AI solutions that support business growth and operational excellence. In this role, you will analyze complex datasets, build and optimize machine learning models, generate actionable business insights, and collaborate with cross-functional teams to solve real-world business challenges. The ideal candidate is passionate about data, analytics, and emerging AI technologies, with the ability to translate technical findings into practical recommendations that create measurable business impact. Key Responsibilities: Collaborate with cross-functional teams to understand business challenges and develop AI- and data-driven solutions. Collect, clean, preprocess, and integrate structured and unstructured data from multiple sources. Perform exploratory data analysis (EDA) to identify trends, patterns, anomalies, and business opportunities. Design, develop, train, validate, and optimize machine learning and predictive models to solve business problems. Conduct feature engineering, model selection, hyperparameter tuning, and performance evaluation to improve model accuracy and reliability. Deploy, monitor, and maintain machine learning models in production environments, ensuring scalability and performance. Develop analytical dashboards, reports, and visualizations to communicate model outputs and business insights effectively. Ensure data quality, consistency, governance, and integrity throughout the analytics and machine learning lifecycle. Present technical findings and actionable recommendations to both technical and non-technical stakeholders. Research and evaluate new machine learning techniques, AI technologies, and industry best practices to drive continuous innovation. Requirements: Bachelor's degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, Artificial Intelligence, or a related field. Minimum 3 years of proven experience as a Data Scientist, Machine Learning Engineer, or in a related role. Strong proficiency in Python and SQL for data processing, statistical analysis, machine learning, and data engineering. Experience processing and analyzing data from ERP systems (e.g., SAP, Oracle, Microsoft Dynamics, or similar). Experience processing and analyzing industrial operational data from SCADA, DCS, PLC, Historian databases, and IoT sensors, preferably in mining, mineral processing, or manufacturing environments. Experience with machine learning libraries and frameworks such as Pandas, NumPy, Scikit-Learn, XGBoost, TensorFlow, PyTorch, or similar. Strong understanding of statistics, feature engineering, predictive modeling, model evaluation, and data mining techniques. Familiarity with cloud platforms (GCP, AWS, or Azure), data warehouse solutions (e.g., BigQuery, Snowflake), and MLOps practices is a plus. Strong analytical, problem-solving, and communication skills with the ability to translate complex data into actionable business insights. Knowledge of mining operations, mineral processing, and industrial analytics is highly preferred.