Senior Data Scientist

Job description / Role

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).

Generative AI expertise: Hands-on experience with generative AI technologies, including building proof of concepts or solutions using large language models or other generative frameworks.

Technical skills and competencies

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.