Make more Creative Job Post Content< Senior Data Scientist (Machine Learning)
- Responsibilities:
At Fluence, we’re not just building the tools for a cleaner, more sustainable world — we’re leading the charge. As a global market leader in energy storage and renewables optimization, we’ve deployed over 3.4 GW of energy storage across 29 markets and optimized more than 4.5 GW of renewable assets. Through innovation, data, and cutting-edge AI solutions like our Fluence IQ platform, we’re empowering a more resilient, sustainable energy future.
Ready to drive transformation in the energy sector? Join us as a Senior Data Scientist (Machine Learning) and power up your potential.
Your Impact
As a Senior Data Scientist specializing in Machine Learning, you’ll bring groundbreaking forecasting capabilities to our Mosaic platform, optimizing renewable energy and battery storage assets for global electricity markets. Your expertise will fuel smarter, more adaptive systems, enhancing how we predict demand, price, and renewable outputs.
This isn’t just a job — it’s a chance to redefine energy.
What You’ll Own:
- Advanced Forecasting Models: Design and deploy statistical and machine learning models for demand, price, and renewable energy predictions. Incorporate probabilistic scenarios to reflect real-world uncertainty.
- Next-Level Techniques: Use ensemble-based methods and self-correcting models to dynamically improve forecast accuracy.
- Market Dynamics Analysis: Dive deep into electricity market trends to uncover shifting dynamics and refine forecasting models.
- Scalable Solutions: Build containerized environments (Docker, Kubernetes) and serverless deployments (AWS Lambda) for efficient model training and inference.
- Data Engineering Excellence: Architect robust ETL pipelines, streamline data workflows, and define schemas that ensure seamless integration.
- Collaboration at Scale: Work closely with engineers, product managers, and other data scientists to embed your solutions into transformative energy applications.
Why You?
You’re not just a data scientist — you’re a problem-solver, innovator, and collaborator. You thrive on tackling complex challenges, love turning data into actionable insights, and are passionate about shaping a sustainable energy future.
What You’ll Bring:
- A Bachelor’s degree with 5+ years, Master’s with 3+ years, or PhD with 2+ years of experience developing advanced forecasting models.
- Expertise in time-series forecasting techniques (statistical, machine learning, and deep learning).
- A deep understanding of stochastic processes and probabilistic modeling.
- Advanced Python skills, including feature engineering, model training, and workflow management.
- Experience with modern software practices (Git, CI/CD pipelines, Agile development).
- Excellent communication skills to articulate technical concepts to diverse teams.
Even Better If You Have:
- A Master’s or PhD in a related field like Computer Science, Statistics, or Electrical Engineering.
- Energy industry experience, especially in deregulated markets (e.g., NEM, CAISO, ERCOT).
- Proficiency with AWS (SageMaker, Step Functions), Docker, and Kubernetes.
- A track record of building ETL pipelines and managing data at scale.
- Expertise in multivariate time-series modeling and dependence structure analysis.
