Energy Analytics Data Scientist | Forecasting & Insights

Placements24; Waukee (IA); On-site; USD 55,000 - 79,000; Full time

Job summary

Placements24 seeks a Data Scientist to join their energy analytics team in Paarl. You will analyze large energy datasets, build predictive models for demand and optimization, and translate results into actionable strategies for generation, distribution, and consumption.

Collaborate with engineers, operations, and business units to drive sustainability and efficiency across the energy landscape, using Python/R, SQL, and big data tools to deliver impact.

Qualifications

• Master's or Ph.D. in a quantitative field such as data science, statistics or CS.
• Minimum 4 years of professional experience as a Data Scientist with energy data.
• Strong Python or R skills and data libraries (Pandas, Scikit-learn, TensorFlow).
• Experience with SQL databases and big data technologies (Spark, Hadoop).

Responsibilities

• Collect, clean, and process large energy-related datasets from various sources.
• Develop and deploy ML models for load forecasting, anomaly detection, and demand prediction.
• Perform statistical analysis and visualize outcomes to reveal trends and insights.
• Collaborate with domain experts to define analytical problems and solutions.
• Communicate findings effectively to technical and non-technical stakeholders.
• Contribute to building data infrastructure and analytical tooling.

Skills

Python

R

Pandas

Scikit-learn

TensorFlow

SQL

Spark

Hadoop

Statistics

Data mining

Education

Master's or PhD in Data Science, Statistics, Computer Science, or related field

Tools

Spark

Hadoop

TensorFlow

Job description

Placements24 seeks a Data Scientist to join their energy analytics team in Paarl. You will analyze large energy datasets, build predictive models for demand and optimization, and translate results into actionable strategies for generation, distribution, and consumption.

Collaborate with engineers, operations, and business units to drive sustainability and efficiency across the energy landscape, using Python/R, SQL, and big data tools to deliver impact.