At a Glance
- Tasks: Leverage advanced analytics and machine learning to optimise processes in energy storage.
- Company: Join AESC, a global leader in high-performance battery manufacturing for EVs.
- Benefits: Competitive salary, flexible working options, and opportunities for professional growth.
- Other info: Collaborative environment with a focus on cutting-edge technology and career advancement.
- Why this job: Make a real impact on sustainability through innovative data solutions.
- Qualifications: Advanced degree in Data Science or related field with 5+ years of experience.
The predicted salary is between 60000 - 80000 € per year.
AESC is a global leader in the development and manufacturing of high-performance batteries for zero-emission electric vehicles (EV) and energy storage systems (ESS). Founded in Japan in 2007 and headquartered in Yokohama, AESC has built a strong global manufacturing footprint over the past 15 years to serve key markets. The company currently operates gigafactories across Japan, the United States, the United Kingdom, France, Spain, and China. AESC has been consistently recognized by leading battery research institutions as a Global Tier 1 Battery Manufacturer. In the energy storage sector, AESC ranked among the Top 3 globally in energy storage cell shipments in 2024, according to authoritative industry sources. Led by a diverse and experienced management team, AESC employs more than 14,000 professionals worldwide. The company combines state-of-the-art technology, Japanese craftsmanship, and a strong track record in safety to deliver advanced battery solutions.
We are seeking a Senior Data Scientist to apply advanced analytics, machine learning, and language models to optimize processes, operations, safety, and decision-making across AESC’s global energy storage business. The focus of this role is not low-level control systems, but rather system-level intelligence and process optimization across the full BESS lifecycle, including:
- Manufacturing and quality processes
- Operations and maintenance workflows
- Safety, reliability, and risk management
- Planning, diagnostics, and decision support
- Knowledge automation and engineering productivity
This role will leverage large-scale operational, manufacturing, and engineering datasets, as well as unstructured data (documents, logs, procedures, tickets), using ML and language models to improve efficiency, consistency, and outcomes across the organization and its deployed assets.
Key Responsibilities
- Process & Operations Optimization
- Develop data-driven models to optimize operational and maintenance processes, including:
- Failure detection and root-cause analysis
- Maintenance planning and prioritization
- Asset availability and reliability improvement
- Identify inefficiencies and variability in technical and operational workflows and propose AI-enabled improvements
- Safety, Reliability & Risk Analytics
- Build models to:
- Detect early safety and reliability risks
- Analyze incident, alarm, and event data
- Support predictive and preventative risk management
- Quantify uncertainty and risk to support engineering and operational decision-making
- Apply large language models (LLMs) to:
- Automate and standardize engineering and operational processes
- Extract insights from unstructured data (reports, logs, procedures, contracts, standards)
- Improve knowledge retrieval, decision consistency, and response time
- Design AI tools that support:
- Engineering teams
- Operations and service teams
- Commercial and proposal teams
- Design and deliver data products that provide:
- Actionable insights rather than dashboards
- Clear recommendations tied to business outcomes
- Translate complex analytical outputs into clear narratives for technical and non-technical stakeholders
- Develop short-term and medium-term forecasting models for:
- Asset behavior and performance
- Operational demand and resource planning
- Support scenario analysis and “what-if” evaluations for planning and optimisation
- Work closely with:
- Engineering, manufacturing, and operations teams
- Software and digital platform teams
- Ensure models and tools are deployable, maintainable, and scalable
- Monitor deployed model performance and continuously improve outcomes
Required Qualifications & Experience
- Advanced degree (MSc or PhD preferred) in:
- Data Science
- Applied Mathematics
- Computer Science
- Electrical / Energy Engineering
- Physics
- 5+ years’ experience applying ML/AI to real-world systems
- Demonstrated delivery of models
Technical Skills (Must-Have)
- Strong programming skills in Python (mandatory)
- Experience with:
- Time-series analysis and forecasting
- Statistical modelling and ML algorithms
- Model validation and performance monitoring
- Experience working with large datasets and distributed systems
- Solid understanding of model lifecycle management
- Nice-to-Have
- Experience with:
- PyTorch / TensorFlow
- Optimization solvers
- Digital twins or physics-informed ML
- Knowledge of DevOps, APIs, and cloud platforms
- Exposure to forecasting, bidding, or operational optimization in energy markets
Personal Attributes
- Comfortable working across software, hardware, and power-system teams
- Strong analytical and systems-thinking mindset
- Able to explain complex models to non-data-scientists
- Curious, pragmatic, and impact-focused
Senior Data Scientist in Liverpool employer: AESC
AESC is an exceptional employer, offering a dynamic work environment that fosters innovation and collaboration in the rapidly evolving field of energy storage and electric vehicle technology. With a strong commitment to employee growth, AESC provides opportunities for professional development and engagement in cutting-edge projects, all while promoting a culture of safety and excellence. Located in Europe, employees benefit from being part of a globally recognized leader in battery manufacturing, contributing to sustainable solutions that power the future.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Scientist in Liverpool
✨Tip Number 1
Network like a pro! Reach out to current employees at AESC on LinkedIn or other platforms. Ask them about their experiences and any tips they might have for landing a role like Senior Data Scientist. Personal connections can make a huge difference!
✨Tip Number 2
Prepare for that take-home assessment! Brush up on your machine learning skills and be ready to showcase your problem-solving abilities. Practice with similar datasets and scenarios to ensure you're confident when the time comes.
✨Tip Number 3
Show off your projects! If you've worked on relevant data science projects, make sure to highlight them in your conversations. Discuss how you applied ML techniques to solve real-world problems, especially in energy or manufacturing contexts.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows your genuine interest in joining AESC and being part of their innovative team.
We think you need these skills to ace Senior Data Scientist in Liverpool
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Senior Data Scientist role. Highlight your experience with machine learning, data analysis, and any relevant projects that showcase your skills in optimising processes and operations.
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about AESC's mission and how your background aligns with the role. Be specific about how you can contribute to their energy storage business.
Showcase Your Technical Skills:Don’t forget to highlight your programming skills, especially in Python, and any experience with ML algorithms or large datasets. Mention any tools or frameworks you’ve used that are relevant to the job description.
Apply Through Our Website:We encourage you to apply through our website for a smoother application process. It’s the best way for us to receive your application and ensure it gets the attention it deserves!
How to prepare for a job interview at AESC
✨Know Your Data Science Stuff
Make sure you brush up on your machine learning algorithms, statistical modelling, and programming in Python. AESC is looking for someone who can apply these skills to real-world systems, so be ready to discuss your past projects and how you've used data to drive decisions.
✨Understand the Industry
Familiarise yourself with the electric vehicle and energy storage sectors. Knowing about AESC's role as a global leader in battery manufacturing will help you connect your skills to their needs. Be prepared to discuss trends in the industry and how they might impact data science applications.
✨Prepare for Technical Questions
Expect some technical questions or case studies during the interview. Practice explaining complex models and your thought process clearly, especially to non-data-scientists. This will show that you can communicate effectively across teams, which is crucial for the role.
✨Show Your Problem-Solving Skills
AESC values innovation and efficiency, so come prepared with examples of how you've identified inefficiencies and proposed AI-enabled improvements in your previous roles. Highlight your analytical mindset and how you've used data to optimise processes and decision-making.
