Data Scientist - Energy Analytics

Placements24; Randburg; Hybrid; ZAR 600,000 - 900,000; Full time

Benefits offered by this job

Health insurance

Paid time off

Remote work

Professional development

Conference access

Job summary

Placements24 is seeking a Data Scientist focused on Energy Analytics to join a fully remote team. You will leverage advanced statistical modeling, machine learning, and data mining to extract insights from oil and gas data and drive data-informed decisions.

You will work with engineers and geoscientists, build scalable models, create dashboards, and stay ahead of industry trends through continuous learning.

Qualifications

• Master's or Ph.D. in Data Science, Statistics, CS, or related field.
• Proven experience with analytical projects in data science.
• Strong programming skills in Python or R and libraries.
• Experience with big data technologies (Spark/Hadoop) and SQL databases.

Responsibilities

• Develop and implement machine learning models for predictive maintenance, production optimization, and anomaly detection.
• Analyze large, complex datasets from various sources to identify trends and patterns.
• Design and execute experiments to evaluate proposed solutions.
• Collaborate with domain experts to define data requirements and interpret findings.
• Build data visualizations and dashboards to communicate insights to stakeholders.
• Stay updated with advances in data science and energy analytics.

Skills

Python

R

Machine Learning

Statistics

Data Visualization

Communication

Education

Master's or Ph.D. in Data Science/Statistics/CS

Tools

scikit-learn

TensorFlow

Pandas

Apache Spark

Hadoop

SQL

Job description

About the Role

Our client is seeking a talented Data Scientist with a focus on Energy Analytics to join their innovative, fully remote team. You will leverage advanced statistical modeling, machine learning, and data mining techniques to extract actionable insights from complex datasets related to oil and gas operations. This role is critical in driving data-informed decision-making, optimizing operational efficiency, and identifying new opportunities for growth. If you are passionate about solving challenging problems using data and thrive in a flexible, remote-first environment, this is the perfect opportunity for you to make a significant impact.

Key Responsibilities

• Develop and implement machine learning models for predictive maintenance, production optimization, and anomaly detection.
• Analyze large, complex datasets from various sources (e.g., production, seismic, operational logs) to identify trends and patterns.
• Design and execute A/B tests and other experiments to evaluate the impact of proposed solutions.
• Collaborate with domain experts (engineers, geoscientists) to define data requirements and interpret findings.
• Build data visualizations and dashboards to communicate insights effectively to both technical and non-technical stakeholders.
• Stay abreast of the latest advancements in data science, machine learning, and energy analytics.

Requirements

• Master's or Ph.D. in Data Science, Statistics, Computer Science, or a related quantitative field.
• Proven experience as a Data Scientist with a strong portfolio of analytical projects.
• Proficiency in programming languages such as Python or R, and relevant libraries (e.g., scikit-learn, TensorFlow, Pandas).
• Experience with big data technologies (e.g., Spark, Hadoop) and SQL databases.
• Strong understanding of statistical modeling, machine learning algorithms, and data mining techniques.
• Excellent communication and collaboration skills, with experience working in a remote team environment.

Benefits

• Highly competitive salary and performance bonuses.
• Comprehensive health, dental, and vision insurance.
• Generous paid time off and flexible working hours.
• Fully remote work arrangement, offering significant work-life balance.
• Opportunities for continuous learning, professional development, and attending conferences.
• Access to powerful computing resources and cutting-edge analytical tools.