Senior Data Scientist, Energy Analytics — Forecasting

Placements24; South Africa; On-site; ZAR 1,200,000 - 1,900,000; Full time

Benefits offered by this job

Competitive salary

Equity opportunity

Medical & retirement benefits

Professional development budget

Job summary

Placements24 in Paarl seeks a Senior Data Scientist specializing in Energy Analytics to leverage large energy datasets, build predictive models, and develop data-driven solutions that optimize energy generation, distribution, and consumption.

The role requires a PhD or Master’s in a quantitative field, 5+ years of experience, and proficiency with Python or R, ML libraries, and big data on cloud platforms.

Qualifications

• PhD or Master's in a quantitative field.
• Minimum 5 years of data science experience in energy.
• Proficiency in Python or R and ML libraries.
• Experience with big data tech (Spark/Hadoop) and cloud platforms (AWS/Azure/GCP).

Responsibilities

• Develop ML models for energy forecasting, anomaly detection, and demand prediction.
• Analyze energy datasets to identify trends, patterns, and insights for business strategy.
• Design and build data pipelines for large-scale energy data collection and processing.
• Collaborate with domain experts, engineers, and stakeholders to define analytical problems and deliver solutions.
• Communicate findings and recommendations through data visualizations and presentations to diverse audiences.

Skills

Energy analytics

Machine learning

Python

R

Statistics

Data engineering

Communication

Education

Ph.D. or Master's in Data Science or related field

Tools

Spark

Hadoop

TensorFlow

PyTorch

AWS

Azure

GCP

Job description

Placements24 in Paarl seeks a Senior Data Scientist specializing in Energy Analytics to leverage large energy datasets, build predictive models, and develop data-driven solutions that optimize energy generation, distribution, and consumption.

The role requires a PhD or Master’s in a quantitative field, 5+ years of experience, and proficiency with Python or R, ML libraries, and big data on cloud platforms.