Senior Data Insights Specialist

Job Overview

As a Principal/Staff Data Scientist, you will spearhead data-driven initiatives to optimize exploration, production, and operational efficiency.

Your role involves building predictive models, deploying machine learning algorithms, and leading a team to solve complex challenges.

Responsibilities

• Lead advanced analytics projects, from defining business problems to deploying machine learning models at scale.
• Architect and build predictive models, statistical algorithms, and machine learning systems to solve complex business challenges.
• Provide technical leadership and mentorship to junior data scientists, promoting best practices and guiding technical development.
• Innovate new methodologies in machine learning and AI, staying at the forefront of emerging tools and techniques.
• Lead cross-functional teams, ensuring alignment and seamless integration between data science, engineering, and business teams.
• Implement robust data governance, validation, and quality assurance processes to ensure data integrity and reliability.
• Partner with data engineering and IT teams to build scalable, automated data pipelines that support analytics initiatives.
• Present complex data insights and machine learning results to non-technical stakeholders, ensuring clarity and business relevance.
• Drive the design and execution of experiments, A/B tests, and statistical analyses to measure and optimize data-driven decisions.
• Ensure compliance with regulatory requirements, data security, and governance protocols when building analytics solutions.
• Understand client needs and provide tailored, strategic solutions that align with business objectives.
• Build strong relationships by clearly communicating technical concepts and managing expectations.
• Actively participate in recruiting top technical talent for the team.
• Collaborate with the sales team in presales activities, identifying client needs and providing technical expertise.
• Define and implement analytics strategies to support exploration, drilling, and production goals.
• Oversee data collection, cleaning, and integration from diverse sources.
• Ensure data accuracy, consistency, and security while adhering to industry compliance standards.
• Design and implement advanced machine learning models for predictive maintenance, reservoir simulations, and production optimization.
• Develop algorithms for seismic data interpretation, reservoir characterization, and well-performance forecasting.
• Optimize workflows using natural language processing for unstructured data.
• Conduct exploratory data analysis to identify trends, anomalies, and optimization opportunities.
• Utilize geospatial analysis and geostatistical techniques to interpret geological and geophysical data.
• Implement real-time data analytics for drilling, well monitoring, and production enhancement.
• Lead the adoption of cloud-based platforms for scalable computation.
• Drive automation of repetitive tasks using advanced scripting and machine learning pipelines.
• Mentor junior data scientists and engineers, fostering innovation and excellence.
• Collaborate with engineers, geophysicists, and reservoir managers to translate business challenges into analytics solutions.
• Communicate technical findings through visualizations and reports.
• Develop optimization models for energy efficiency, cost reduction, and supply chain logistics.
• Enhance drilling accuracy and reduce downtime through predictive analytics.
• Implement risk assessment models to improve safety and compliance standards.
• Expertise in Python, R, MATLAB, and SQL for statistical modelling and data analysis.
• Proficient in machine learning libraries and big data tools.
• Familiarity with visualization tools like Power BI or Tableau.
• Familiarity with domain-specific software like Petrel or Schlumberger's Decision Space.
• Advanced degree (master's or PhD) in Data Science, Computer Science, or a related field.
• 7+ years of experience in data science.
• Demonstrated success in leading analytics projects.
• Deep knowledge of machine learning and statistical modeling.
• Strong programming and data engineering skills.
• Excellent problem-solving and communication abilities.
• Proven track record of innovation in multiple industries.

Requirements

• Advanced degree in Data Science or a related field.
• 7+ years of experience in data science.
• Demonstrated success in leading analytics projects.
• Deep knowledge of machine learning and statistical modeling.
• Strong programming and data engineering skills.
• Excellent problem-solving and communication abilities.
• Proven track record of innovation in multiple industries.