Data Scientist

Role Summary

The Data Scientist will be responsible for analyzing complex datasets, developing predictive models, and delivering actionable insights to support business and operational decision-making. The role involves working closely with cross-functional teams to build machine learning solutions, optimize production processes, and drive innovation through advanced analytics and AI technologies.

Key Responsibilities

• Collect, clean, preprocess, and analyze structured and unstructured datasets from multiple data sources.
• Develop, validate, and deploy predictive and machine learning models using Python-based frameworks.
• Design machine learning algorithms for production optimization, anomaly detection, forecasting, and analytical use cases.
• Perform feature engineering, hyperparameter tuning, and model performance optimization.
• Collaborate with geologists, engineers, business stakeholders, and technical teams to deliver actionable insights.
• Build and maintain production-ready machine learning solutions and analytical pipelines.
• Work with data engineering teams to deploy models on cloud or on-premise environments.
• Create visualizations, dashboards, and analytical reports for technical and non-technical stakeholders.
• Stay updated with the latest trends in AI, machine learning, and data science technologies.
• Mentor junior team members and contribute to continuous improvement initiatives.

Qualifications & Experience

• Bachelor's or Master's Degree in Data Science, Computer Science, Engineering, Statistics, or related field.
• Minimum 3 years of experience in Data Science, Machine Learning, or Advanced Analytics roles.
• Strong programming skills in Python with experience in Pandas, NumPy, and scikit-learn.
• Hands-on experience with TensorFlow, PyTorch, and machine learning model development.
• Experience with SQL and NoSQL databases.
• Exposure to AWS, Azure, or GCP cloud platforms for data storage and model deployment.
• Experience with data visualization tools such as Matplotlib, Seaborn, and Plotly.
• Oil & Gas domain experience or exposure to upstream/downstream datasets is an added advantage.
• Familiarity with tools such as Petrel or Eclipse is beneficial.
• Strong analytical thinking, problem-solving, communication, and stakeholder management skills.