Senior Data Scientist

at  Evergen

Company Description
At Evergen, our mission is to orchestrate over 10GW of distributed energy assets globally, accelerating the world’s transition to renewable energy. We lead the way in renewable energy optimisation, helping the electricity grid operate more efficiently while creating value for individual asset owners.
Evergen is the software heart beating inside a “virtual power plant” (VPP). We optimise and orchestrate batteries, EVs, hot water systems, solar systems and other technologies to collectively support the electricity grid, and in so doing we increase the uptake of renewable energy and create additional value for individual asset owners.
Job Description
As part of the Data Science team, you will collaborate with a close-knit group of skilled professionals focused on advancing renewable energy solutions. Your role will involve developing innovative strategies and tools to optimise energy systems, ensuring they are both efficient and sustainable. Together, you will contribute to creating impactful solutions that drive the future of renewable energy technologies.

Key Responsibilities

• Gather, clean, and preprocess large datasets from various sources, including telemetry from consumer energy resources, IOT devices, weather data, and market information.
• Train, test, and validate machine learning models
• Experiment with novel approaches to solve problems and innovate on ways to add value to the energy system
• Perform analysis of product ideas using a variety of tools including simulation and conduct deep dives into the performance of systems to provide feedback to clients and customers
• Work closely with software developers, product managers, data engineers, and domain experts to design and develop solutions to problems utilising data science, ML and optimisation
• Evaluate model performance and continuously improve based on feedback and real-world data, and undertake hypothesis testing to evaluate changes
• Develop dashboards and reports to communicate insights and support decision-making.
• Provide expertise on mathematical concepts and statistical techniques to improve data driven outcomes for clients
• Stay updated with the latest trends in data science, AI, and renewable energy technologies
• Building tools and algorithms to support renewable energy initiatives such as demand forecasting and energy storage management

Qualifications

You are passionate about renewable energy and thrive in a fast-paced, innovative environment. In addition to this, you will bring:

• 2+ years of data science experience
• Bachelor’s, Master’s, or Ph.D. in: Computer Science, Data Science, Artificial Intelligence, Machine Learning, Electrical/mechatronic Engineering (with a focus on data systems or signal processing), Physics (with a computational focus), Applied Mathematics and statistics, or similar
• Data Analysis & Statistics: Proficiency in statistical analysis, data cleaning/imputation, and exploratory data analysis techniques
• Machine Learning: Experience with supervised and unsupervised learning, time-series forecasting, Hypothesis testing, classification, clustering, and anomaly detection techniques
• Programming Languages: Proficiency in Python, with knowledge of data science libraries (e.g., Pandas, NumPy, Scikit-learn, PyTorch, PyDantic, Jupyter Notebooks)
• Data Engineering: Proficient with SQL, data pipelines, and ETL processes
• Visualisation Tools: Experience with visualization libraries and tools (e.g., Matplotlib, Seaborn, Plotly, Tableau, PowerBI, Quicksight, streamlit)
• Collaboration & Communication: Strong presentation skills and ability to communicate insights and collaborate with cross-functional teams including engineers, product managers, and stakeholders

BONUS SKILLS

• Domain Knowledge: Understanding of load and PV forecasting, Energy market operation, electrical systems and/or consumer energy resources.
• Software development: Experience with Python, RESTful APIs (FastAPI), and Test Driven Development
• Big Data & Cloud Technologies: Knowledge of cloud platforms (AWS, Azure, GCP), distributed computing tools (Spark, Hadoop), and data storage solutions.
• Optimisation knowledge: Understanding of convex, linear, and mixed integer linear optimization techniques and their implementation using PyOmo or Ortools as well as an understanding of model predictive control
• Proven ability to lead, mentor, and collaborate effectively
  Additional Information
  Our team is a diverse group of brilliant, curious, and passionate individuals working together to solve some of the world’s most pressing energy challenges.
  If you’re excited to make a real impact on the future of energy, we’d love to hear from you! Submit your application today and help us build a sustainable energy future

• Gather, clean, and preprocess large datasets from various sources, including telemetry from consumer energy resources, IOT devices, weather data, and market information.
• Train, test, and validate machine learning models
• Experiment with novel approaches to solve problems and innovate on ways to add value to the energy system
• Perform analysis of product ideas using a variety of tools including simulation and conduct deep dives into the performance of systems to provide feedback to clients and customers
• Work closely with software developers, product managers, data engineers, and domain experts to design and develop solutions to problems utilising data science, ML and optimisation
• Evaluate model performance and continuously improve based on feedback and real-world data, and undertake hypothesis testing to evaluate changes
• Develop dashboards and reports to communicate insights and support decision-making.
• Provide expertise on mathematical concepts and statistical techniques to improve data driven outcomes for clients
• Stay updated with the latest trends in data science, AI, and renewable energy technologies
• Building tools and algorithms to support renewable energy initiatives such as demand forecasting and energy storage managemen