Senior Data Scientist

Overview

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

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. 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.

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