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For Companies At a Glance
- Tasks: Analyse data, develop analytics frameworks, and optimise energy consumption for real-world impact.
- Company: Fast-growing tech company focused on sustainability and innovation.
- Benefits: Competitive salary, hybrid work model, and opportunities for professional growth.
- Other info: Collaborative environment with a focus on continuous learning and development.
- Why this job: Make a difference in energy efficiency while working with cutting-edge technology.
- Qualifications: Strong analytical skills, proficiency in Python or R, and a degree in a quantitative field.
The predicted salary is between 65000 - 75000 £ per year.
Join a fast-growing technology company providing award-winning solutions that help retailers and building owners optimise energy usage, automate operations, and reduce environmental impact. Their platform integrates IoT, telemetry, and AI to deliver predictive insights across multiple sites globally. Working here means applying data science to real-world challenges, improving system efficiency and reliability for high-profile clients.
What You’ll Be Doing
- Analyse diverse datasets from connected building assets, energy systems, and environmental sensors.
- Develop, test, and deploy advanced analytics frameworks and machine learning models.
- Translate R&D and exploratory analysis into production-ready algorithms and reusable components.
- Design experiments and predictive models to optimise energy consumption and building performance.
- Communicate insights clearly to technical and non-technical stakeholders.
- Collaborate with internal and client-facing teams to align data solutions with business needs.
- Stay up to date with emerging AI, machine learning, and energy technology trends.
- Contribute to internal best practices, documentation, and team knowledge sharing.
Ideal Background
- Strong analytical mindset and passion for deriving actionable insights from complex data.
- Proficient in Python or R (pandas, NumPy, scikit-learn, TensorFlow or equivalent) and SQL.
- Experience as a data scientist on client-facing software solutions, ideally in optimisation or energy-focused domains.
- Solid foundation in statistical analysis, machine learning (regression, classification, clustering, time series).
- Degree in a quantitative discipline such as Mathematics, Statistics, Computer Science, Engineering, or Physics.
- Desirable: MSc or PhD in a quantitative field.
- Cloud-based ML deployment experience.
- Version control experience (Git) and Agile collaboration.
- Exposure to IoT, smart buildings, or energy management systems.
Marketing Data Scientist in Lisburn employer: ANSON MCCADE
Contact Detail:
ANSON MCCADE Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Marketing Data Scientist in Lisburn
✨Tip Number 1
Network like a pro! Reach out to people in the industry on LinkedIn or at local meetups. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data science projects, especially those related to energy optimisation or machine learning. This will give potential employers a taste of what you can do.
✨Tip Number 3
Prepare for interviews by brushing up on your technical skills and being ready to discuss your past projects. Practice explaining complex concepts in simple terms, as you'll need to communicate with both technical and non-technical folks.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got some fantastic opportunities waiting for you, and applying directly can sometimes give you an edge over other candidates.
We think you need these skills to ace Marketing Data Scientist in Lisburn
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Marketing Data Scientist role. Highlight your experience with Python, SQL, and any relevant projects that showcase your analytical skills. We want to see how your background aligns with our needs!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about data science and how you can contribute to our mission. Be sure to mention any experience with energy optimisation or machine learning that relates to the role.
Showcase Your Projects: If you've worked on any interesting projects, especially those involving IoT or predictive analytics, make sure to include them in your application. We love seeing real-world applications of your skills, so don’t hold back!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows you’re keen on joining our team!
How to prepare for a job interview at ANSON MCCADE
✨Know Your Data Science Tools
Make sure you're well-versed in Python or R, especially libraries like pandas and scikit-learn. Brush up on your SQL skills too, as you'll likely be asked to demonstrate your ability to manipulate and analyse data during the interview.
✨Showcase Real-World Applications
Prepare examples of how you've applied data science to solve real-world problems, particularly in optimisation or energy-focused projects. This will help you illustrate your analytical mindset and how you derive actionable insights from complex datasets.
✨Communicate Clearly
Practice explaining your findings and methodologies in a way that both technical and non-technical stakeholders can understand. Being able to communicate complex ideas simply is crucial, especially when collaborating with diverse teams.
✨Stay Updated on Trends
Familiarise yourself with the latest trends in AI, machine learning, and energy technology. Showing that you're proactive about staying informed will demonstrate your passion for the field and your commitment to continuous learning.