Remote Data Scientist - Energy Market Analytics

Placements24; Bloemfontein; Hybrid; ZAR 1,000,000 - 1,300,000; Full time

Benefits offered by this job

Fully remote work

Competitive salary with bonus

Health & wellness benefits

Professional development

Job summary

Placements24 is seeking a Remote Data Scientist to join their analytics team focused on the energy market. You will analyze large datasets, build predictive models, and uncover trends to optimize trading strategies, forecasting, and operations.

This fully remote role offers collaboration with cross-functional teams in a virtual setting. The ideal candidate holds a Master’s or PhD in a quantitative field, has 5+ years of experience, and is proficient in Python or R with ML libraries.

Qualifications

• Master's degree or PhD in a quantitative field.
• 5+ years experience as Data Scientist building and deploying predictive models.
• Proficiency in Python or R with relevant libraries.
• Experience with large datasets and distributed computing (Spark).
• Excellent remote communication and presentation skills.

Responsibilities

• Collect, clean, and process large energy datasets (consumption, generation, prices).
• Develop, validate, deploy ML models for demand forecasting and price prediction.
• Perform EDA to identify patterns in energy market data.
• Design and run A/B tests to evaluate model performance and business impact.
• Visualize model results for technical and non-technical audiences.
• Collaborate with traders, operations, and stakeholders to deliver insights.

Skills

Python

R

statistics

machine learning

data mining

EDA

communication skills

Education

Master's or PhD in Data Science, Statistics, CS, Economics

Tools

scikit-learn

TensorFlow

PyTorch

Spark

Job description

About the Role

Our client is seeking a talented and innovative Remote Data Scientist to join their growing analytics team, focusing on the energy market. This is a fully remote position, allowing you the flexibility to work from your preferred location while contributing to critical data-driven insights for the company. You will be responsible for analyzing vast datasets, developing predictive models, and uncovering trends to optimize energy trading strategies, demand forecasting, and operational efficiency. This role offers a unique opportunity to leverage advanced analytical techniques in a dynamic and rapidly evolving industry, working collaboratively with cross-functional teams in a virtual setting.

Key Responsibilities

• Collect, clean, and process large and complex datasets related to energy consumption, generation, and market prices.
• Develop, validate, and deploy machine learning models for demand forecasting , price prediction, and anomaly detection.
• Perform exploratory data analysis (EDA) to identify patterns and insights within the energy market data .
• Design and implement A/B tests and other experiments to evaluate model performance and business impact.
• Visualize data and model results effectively for technical and non-technical audiences.
• Collaborate with energy traders, operations managers, and other stakeholders to understand their needs and deliver actionable insights.

Requirements

• Master's degree or PhD in Data Science, Statistics, Computer Science, Economics, or a related quantitative field.
• Minimum of 5 years of experience as a Data Scientist , with a proven track record in building and deploying predictive models.
• Strong proficiency in programming languages such as 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 working with large datasets and distributed computing frameworks (e.g., Spark).
• Excellent communication and presentation skills, with the ability to explain complex analytical concepts clearly in a remote environment .

Benefits

• Highly competitive salary and attractive bonus structure.
• Comprehensive health and wellness benefits.
• Significant opportunities for professional development and continuous learning.
• Flexible working hours and a fully remote work setup.
• The chance to work with a leading organization in the global energy sector .