Senior Data Scientist - Subsurface Analytics

Placements24; Benoni; Hybrid; ZAR 900,000 - 1,300,000; Full time

Benefits offered by this job

Competitive salary

Health insurance

Generous leave

Professional development budget

Job summary

Placements24 in South Africa seeks a highly analytical Senior Data Scientist specializing in subsurface analytics to join our expanding team. This fully remote role uses ML and statistical modeling on seismic, well logs, and production data to improve exploration success and reservoir performance.

You will collaborate with geoscientists and engineers to translate business challenges into data science problems, communicate findings clearly, and contribute to impactful energy sector projects.

Qualifications

• Master's or PhD in Data Science, Computer Science, Statistics, Petroleum Engineering, or a related quantitative field.
• 5+ years of professional experience as a Data Scientist, with focus on Oil & Gas or subsurface data.
• Proficiency in Python or R and ML libraries (e.g., Scikit-learn, TensorFlow, PyTorch).

Responsibilities

• Develop and implement machine learning models for subsurface characterization, predictive maintenance, and production forecasting.
• Analyze large, diverse datasets (seismic, well logs, production data) to identify patterns and insights.
• Design and conduct A/B tests and experiments to validate hypotheses and model performance.
• Collaborate with domain experts to translate business challenges into data science problems.
• Communicate complex findings and recommendations to technical and non-technical audiences through visuals and reports.

Skills

Analytical thinking

Communication

Problem solving

Education

Master's or PhD in Data Science / CS / Statistics / Petroleum Engineering

Tools

Python

R

Scikit-learn

TensorFlow

PyTorch

AWS

Azure

GCP

Job description

About the Role

Our client is seeking a highly analytical and innovative Senior Data Scientist specializing in subsurface analytics to join their expanding team. This is a fully remote position, offering the flexibility to work from anywhere within the specified region. You will leverage advanced data science techniques, machine learning, and statistical modeling to extract valuable insights from complex subsurface datasets within the Oil & Gas sector. Your work will be instrumental in improving exploration success rates, optimizing reservoir performance, and enhancing operational efficiency. You will collaborate closely with geoscientists, engineers, and other data professionals to drive data-informed decision-making across the organization.

Key Responsibilities

• Develop and implement machine learning models for subsurface characterization, predictive maintenance, and production forecasting.
• Analyze large, diverse datasets (seismic, well logs, production data) to identify patterns and extract actionable insights.
• Design and conduct A/B tests and other experiments to validate hypotheses and model performance.
• Collaborate with domain experts to understand business challenges and translate them into data science problems.
• Communicate complex findings and recommendations clearly to both technical and non-technical audiences through visualizations and reports.

Requirements

• Master's or PhD in Data Science, Computer Science, Statistics, Petroleum Engineering, or a related quantitative field.
• 5+ years of professional experience as a Data Scientist , with a significant focus on the Oil & Gas industry or subsurface data.
• Strong proficiency in programming languages like Python or R, and experience with relevant libraries (e.g., Scikit-learn, TensorFlow, PyTorch).
• Expertise in statistical modeling, machine learning algorithms, and data mining techniques.
• Experience with big data technologies and cloud platforms (e.g., AWS, Azure, GCP).

Benefits

• Highly competitive salary and bonus structure, reflecting remote work and expertise.
• Comprehensive health, dental, and vision insurance coverage, accessible remotely.
• Generous annual leave and a flexible working schedule.
• Professional development budget for courses, conferences, and certifications.
• Opportunity to work on challenging, impactful projects at the forefront of data science in the energy sector.