Data Scientist (Oil & Gas Hydraulics)

We are seeking a skilled Data Scientist with experience in building optimization and machine learning models specifically for oil and gas hydraulics use cases. As a Data Scientist, you will play a critical role in analysing and improving hydraulics processes within the oil and gas industry. Your expertise in data science and machine learning will be instrumental in driving operational efficiency and cost optimization.

Responsibilities

• Develop and implement optimization and machine learning models to improve hydraulics processes in the oil and gas industry.
• Analyse and interpret data related to target flow rates, energy/utility costs, pump efficiency curves, Drag Reducing Agent (DRA) performance curves, DRA QA limits, DRA costs, and pipeline attributes.
• Collaborate with cross-functional teams to identify areas for improvement and apply data-driven solutions.
• Conduct thorough data analysis, feature engineering, and model development to extract actionable insights.
• Utilize advanced statistical techniques and machine learning algorithms to predict and optimize hydraulics performance.
• Stay updated with the latest advancements in data science, machine learning, and optimization methodologies relevant to the oil and gas industry.
• Present findings and recommendations to stakeholders, including technical and non-technical audiences.
• Collaborate with data engineers and IT teams to ensure seamless data integration and model deployment.
  

Requirements

• Bachelor's or master's degree in a relevant field (e.g., Data Science, Computer Science, Petroleum Engineering, or related disciplines).
• Proven experience in building optimization and machine learning models for oil and gas hydraulics use cases.
• Strong familiarity with concepts such as target flow rates, energy/utility costs, pump efficiency curves, DRA performance curves, DRA QA limits, DRA costs, and pipeline attributes.
• Proficiency in data science tools and programming languages, including Python, R, PySpark, DASK, and SQL.
• Solid understanding of statistical analysis, machine learning algorithms, and optimization techniques.
• Experience in data manipulation, cleansing, and feature engineering.
• Ability to work with large datasets and perform exploratory data analysis.
• Strong problem-solving skills and the ability to translate business requirements into data-driven solutions.
• Excellent communication and presentation skills to effectively convey complex findings and recommendations to stakeholders.
• Strong attention to detail, analytical mindset, and a passion for continuous learning and improvement.