Data Scientist Intern supporting analytics and predictive modeling for member growth and market strategy. Collaborating with data scientists and analysts to enhance location intelligence and insights.
About the role
- Senior Data Scientist at Zenobē focusing on smart charging analytics with Python-based modelling and optimisation. Collaborate across teams to optimize EV charging strategy globally.
Responsibilities
- Leading development of our charging strategy optimisation pipeline: writing python code for data processing, physics-based simulation, commercial optimisation and data insight.
- Diving into the operational, commercial and technical details of EV charging sites to tailor our modelling and optimisation pipelines to each customer and geography across our global portfolio, adapting to local constraints and opportunities in each case.
- Managing the roll out of smart charging across our international portfolio and in partnership with business development and customer success colleagues, you’ll use data and expert insight to highlight the value of smart charging to customers and help resolve operational concerns
- Work with large fleet and charging datasets to train machine-learning models for predicting vehicle energy consumption or correlate physics-based models for virtual recreation of charging operations as a digital twin simulation.
- Testing and cloud-deployment of code whilst ensuring alignment of ways of working with other technical teams
- Pairing with other team members contributing to the smart charging codebase and reviewing pull requests to maintain coding standards.
- Strategic planning of the smart charging analytical roadmap, aligning the delivery and dependencies of new features with product managers and balancing customer value delivery with reliability and effort
- Management of team members working in the smart charging domain including work planning, reviewing and 1:1s.
- Engage with onboarding and operational teams to define data requirements and testing plans in support of model development and correlation (e.g. charging or vehicle energy consumption).
- Keep up to date with evolving smart charging opportunities and business cases, and the expanding needs of the business with a growing number of technologies and geographies supported.
- Drive innovation in our modelling, analysis and data insight approaches through L&D and trialing novel concepts.
- Actively contribute to Zenobe's commitment to health and safety, wellbeing and sustainability by; integrating these principles into daily responsibilities, ensuring a safe and supportive work environment, promoting both the physical and mental health of self and colleagues, and adopting sustainable and energy-efficient practices to minimize environmental impact.
Requirements
- STEM degree (e.g. engineering, applied physics, data science)
- 4+ years of relevant professional experience working in modelling, simulation, analytics and optimisation preferably in an EV or energy-adjacent domain
- 5+ years’ experience with Python (pandas, scipy, plotly, scikit-learn, and other scientific / data libraries) and it’s developer tooling (e.g. uv, ruff, mypy)
- A pragmatic approach to problem solving, follower of the 80/20 rule balancing outcome with effort and comfortable working with imperfect real-world data
- Solid SDLC and collaborative software practices including GIT for version control, testing, CICD, environment management etc.
- Ability to mentor others on advanced use of Python.
- Technical background with good understanding of the underlying physical principles related to electric vehicles and the energy sector
- Familiarity with energy markets, tariffs, grid services and commercial aspects of the energy sector
- Confidence in working with autonomy, spearheading areas of technical development and representing our technical expertise both internally and externally
- Demonstrable leadership in the planning and delivery of projects, accountability to senior stakeholders and line management of team members
- A working knowledge of data engineering and cloud platform concepts
- Excellent mathematical, analytical and problem-solving ability
- Excellent professional communication, reporting and presentation skills
- Experience with cloud providers and cloud infrastructure deployment (preferably AWS).
Benefits
- Up to 33% annual bonus for being awesome
- 25 days holiday, increasing with length of service up to 30 days, plus bank holidays
- Private Medical Insurance
- £1,500 training budget per year, to ensure you grow as we do
- EV Salary Sacrifice Scheme
- Pension scheme, up to 8% matched contributions
- Enhanced parental leave
- Cash back health plan
- Plus more
Job title
Job type
Experience level
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Not specified
Degree requirement
Tech skills
Location requirements
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