Senior Data Scientist

Accountabilities:

• To participate in the development of data science strategy and tactics to support the company’s strategic objectives to become a data driven company.
• To promote data science & analytics to increase business insights to resolve business problems or support decisions making processes.
• Develop innovative PoCs and end-to-end data analytics solutions with high value adding in terms of business impact.
• Contribute and propose ways to maximize the value of geosciences, operations, HSE, CPD and MP, etc. data.
• To manage relationships with internal and external vendors for data science.

Education:

• Master’s degree in a relevant field such as Data Science, Computer Science, Statistics, Mathematics, or Engineering.

Experience:

• Minimum 6 years of experience in Data Science: Proven track record of developing and implementing machine learning models, advanced analytics solutions, and data-driven decision-making strategies
• Industry Expertise: Experience working in the oil and gas industry, with a strong understanding of its challenges, processes, and data types (e.g., seismic data, production data, reservoir data).
• GenAI Expertise: Hands-on experience with Generative AI technologies, including building PoCs/ solutions using large language models or other generative frameworks.

Technical & Soft Skills:

• Programming Languages: Proficiency in Python is required. Additional experience in Spark is a plus.
• Data Manipulation Tools: Good experience with SQL, Pandas, and other data processing tools.
• Machine Learning Frameworks: Experience with TensorFlow, PyTorch, Scikit-learn, or similar libraries.
• Cloud Platforms: Hands-on experience with cloud services such as Microsoft Azure including their AI and data services is a plus.
• Visualization Tools: Proficiency in Power BI, or similar visualization platforms.
• Big Data Technologies: Familiarity with Hadoop, Spark, or Databricks is an advantage.
• Statistical Analysis: Strong foundation in statistical modeling, hypothesis testing, and predictive analytics.
• Problem-Solving: Proven ability to translate complex business problems into actionable data science solutions.
• Collaboration: Strong track record of cross-functional collaboration, effectively communicating technical concepts, from foundational principles to advanced methodologies to diverse stakeholder audiences.
• Strong stakeholder management: Setting clear expectations, fostering trust through transparent communication, and applying empathy to build lasting, collaborative relationships.

Language proficiency:

• Demonstrates mastery of the English language across spoken, written, and active listening skills, enabling clear, empathetic, and effective communication in diverse professional settings.