Remote Data Scientist: Energy Analytics & Forecasting

Placements24; Bloemfontein; Hybrid; ZAR 900,000 - 1,200,000; Full time

Benefits offered by this job

Competitive salary with bonuses

Fully remote work arrangement

Health and wellness benefits

Professional development budget

Job summary

Placements24 is seeking a skilled Data Scientist specializing in Energy Analytics to join a fully remote team in South Africa. You will develop predictive models, perform advanced statistical analysis, and create dashboards for exploration, production, and operational efficiency.

The ideal candidate holds a Master's or PhD in a quantitative field, with proven DS experience and proficiency in Python/R, SQL, and cloud platforms.

Qualifications

• Master's or PhD in Data Science, Statistics, Computer Science, or related field.
• Proven Data Scientist experience with a strong project portfolio.
• Proficiency in Python or R and libraries (scikit-learn, TensorFlow, Pandas).
• Experience with SQL and large databases; cloud platforms a plus.
• Excellent communication and ability to convey complex findings to non-technical audiences.
• Oil & Gas or energy sector exposure is highly desirable.

Responsibilities

• Develop ML models for production forecasting, anomaly detection, and predictive maintenance.
• Analyze large datasets across exploration, production, and operations for key insights.
• Design dashboards and reports to communicate findings to stakeholders.
• Collaborate with domain experts to translate business problems into DS solutions.
• Clean, process, and transform raw data for analysis; stay current with DS advances.

Skills

Python

SQL

Machine learning

Data analysis

Data visualization

R

Education

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

Tools

scikit-learn

TensorFlow

Pandas

AWS/Azure/GCP

Job description

Placements24 is seeking a skilled Data Scientist specializing in Energy Analytics to join a fully remote team in South Africa. You will develop predictive models, perform advanced statistical analysis, and create dashboards for exploration, production, and operational efficiency.

The ideal candidate holds a Master's or PhD in a quantitative field, with proven DS experience and proficiency in Python/R, SQL, and cloud platforms.