Lead Data Scientist - Energy Analytics

Placements24; Queenstown; Hybrid; NZD 130,000 - 190,000; Full time

Benefits offered by this job

Competitive salary and bonus

Health, dental, and vision insurance

Remote work and flexible schedule

Professional growth opportunities

Job summary

Placements24 is seeking a visionary Lead Data Scientist to spearhead energy analytics initiatives. This fully remote role involves advanced statistical modeling, machine learning, and data mining to extract actionable insights from large energy datasets.

You will guide a team of data scientists and collaborate with stakeholders to drive data-informed decisions. You will lead ML model development for energy demand forecasting and fault prediction, mentor junior members, and stay at the forefront

Qualifications

• PhD or Master’s in Data Science, Statistics, CS, or related quantitative field.
• 8+ years in data science and ML with strong energy sector focus.
• Proficiency in Python or R and libraries (scikit-learn, TensorFlow, PyTorch).
• Experience with big data tech (Spark, Hadoop) and cloud platforms (AWS/Azure/GCP).
• Excellent leadership, communication, and problem-solving skills.

Responsibilities

• Develop and implement ML models for forecasting energy demand, failures, and distribution optimization.
• Lead design and execution of data mining and statistical analysis projects in the energy domain.
• Mentor and manage a team of data scientists; provide technical guidance.
• Communicate findings to technical and non-technical stakeholders with visualizations.
• Stay current with data science, ML, and energy tech advances and drive innovation.

Skills

Leadership

Team leadership

Machine learning

Statistical modeling

Communication

Education

Ph.D. or Master’s in Data Science

Tools

Python

R

scikit-learn

TensorFlow

PyTorch

Spark

Hadoop

AWS

Azure

GCP

Job description

About the Role

Our client is looking for a visionary Lead Data Scientist to spearhead their energy analytics initiatives. This fully remote role involves leveraging advanced statistical modeling, machine learning, and data mining techniques to extract actionable insights from vast datasets related to energy consumption, production, and market dynamics. You will guide a team of data scientists, mentor junior members, and collaborate with stakeholders across the organization to drive data-informed decision-making and innovation in the energy sector. This is a critical leadership position for an individual passionate about using data to solve complex energy challenges and shape the future of energy management.

Key Responsibilities

• Develop and implement cutting-edge machine learning models for forecasting energy demand, predicting equipment failures, and optimizing energy distribution.
• Lead the design and execution of complex data mining and statistical analysis projects within the energy domain.
• Mentor and manage a team of data scientists, providing technical guidance and fostering a collaborative research environment.
• Communicate complex findings and insights to technical and non-technical stakeholders through compelling visualizations and presentations.
• Stay abreast of the latest advancements in data science, machine learning, and energy technologies, and identify opportunities for innovation.

Requirements

• Ph.D. or Master's degree in Data Science, Statistics, Computer Science, or a related quantitative field.
• 8+ years of professional experience in data science and machine learning, with a significant focus on the energy sector .
• Proven expertise in programming languages like Python or R, and proficiency with relevant libraries (e.g., scikit-learn, TensorFlow, PyTorch).
• Experience with big data technologies (e.g., Spark, Hadoop) and cloud platforms (e.g., AWS, Azure, GCP).
• Exceptional leadership, communication, and problem-solving skills.

Benefits

• Highly competitive salary and a generous annual bonus.
• Comprehensive health, dental, and vision insurance.
• 401(k) or equivalent retirement plan with employer match.
• Significant opportunities for professional growth and leadership in a remote setting.
• Contribute to cutting-edge solutions in the evolving energy analytics landscape.