𝗤𝗨𝗔𝗟𝗜𝗙𝗜𝗖𝗔𝗧𝗜𝗢𝗡𝗦 & 𝗘𝗫𝗣𝗘𝗥𝗜𝗘𝗡𝗖𝗘 𝗥𝗘𝗤𝗨𝗜𝗥𝗘𝗗
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.