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- Tasks: Analyse complex data sets and build machine learning models to drive business insights.
- Company: Heatly is a leading software platform revolutionising building modelling and decarbonisation in the UK.
- Benefits: Enjoy flexible working options, a creative team environment, and opportunities for professional growth.
- Why this job: Join a diverse team making a real impact on sustainability through innovative data solutions.
- Qualifications: Bachelor's or Master's in Data Science or related field; experience in data analysis and machine learning required.
- Other info: Ideal for tech-savvy individuals passionate about data and sustainability.
The predicted salary is between 28800 - 48000 £ per year.
Company Description
Heatly is a class leading software platform that is pushing the boundaries of traditional building modelling and helping to streamline the decarbonisation of domestic and commercial building stock on the UK.
Our design team interact with all departments and are responsible for delivering class leading mechanical design methodologies that are then integrated into our online platform.
We have a diverse and creative software team who have successfully delivered award winning zero carbon solutions.
Job Description
Job Overview:
We are seeking a talented Data Scientist to join our growing data team. As a Data Scientist at Heatly, you will analyze complex data sets, build machine learning models, and collaborate with stakeholders across the organization to deliver actionable insights and solutions. You will work with a team of data engineers, analysts, and product managers to translate data into valuable business strategies.
Key Responsibilities:
- Collect, clean, and analyze large datasets from various sources to support business decisions.
- Develop and implement machine learning models and statistical techniques to solve business problems.
- Communicate findings through clear visualizations, reports, and presentations for stakeholders.
- Work with data engineers to ensure the smooth extraction, transformation, and loading (ETL) of data.
- Collaborate with cross-functional teams (e.g., product, marketing, and operations) to design and develop data-driven solutions.
- Optimize models and algorithms for efficiency and scalability.
- Stay current with the latest industry trends and technologies in data science and machine learning.
- Design and conduct A/B tests and other experimental methodologies to evaluate model performance.
- Ensure data quality, integrity, and security across the organization.
Required Qualifications:
- Bachelor\’s or Master\’s degree in Data Science, Computer Science, Mathematics, Statistics, or a related field.
- Proven experience (X+ years) as a Data Scientist, Data Analyst, or a similar role.
- Strong proficiency in programming languages such as Python, R, or SQL.
- Experience with machine learning frameworks (e.g., TensorFlow, PyTorch, scikit-learn).
- Knowledge of data visualization tools (e.g., Tableau, Power BI, or Matplotlib).
- Expertise in statistical analysis and hypothesis testing.
- Familiarity with cloud computing platforms (e.g., AWS, Google Cloud, Azure).
- Strong communication skills with the ability to explain complex data insights to non-technical stakeholders.
- Experience in working with big data tools (e.g., Hadoop, Spark) is a plus.
Preferred Skills:
- Experience in deep learning, NLP, or time-series forecasting.
- Familiarity with data engineering concepts such as data pipelines, database management, and cloud architecture.
- Knowledge of business intelligence tools and concepts.
- Understanding of software development practices such as version control (e.g., Git).
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Data Scientist employer: United Living group
Contact Detail:
United Living group Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist
✨Tip Number 1
Familiarise yourself with Heatly's mission and values. Understanding how your skills as a Data Scientist can contribute to their goal of decarbonising buildings will help you align your discussions during interviews and show your genuine interest in the company.
✨Tip Number 2
Brush up on your machine learning frameworks, especially TensorFlow and PyTorch. Being able to discuss specific projects or models you've worked on using these tools will demonstrate your hands-on experience and technical expertise.
✨Tip Number 3
Prepare to showcase your data visualisation skills. Since communicating findings is crucial for this role, having examples of clear and impactful visualisations you've created will set you apart from other candidates.
✨Tip Number 4
Network with current or former employees of Heatly on platforms like LinkedIn. Engaging with them can provide insights into the company culture and expectations, which can be invaluable during your application process.
We think you need these skills to ace Data Scientist
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience and skills that align with the Data Scientist role at Heatly. Emphasise your proficiency in programming languages like Python or R, and any experience with machine learning frameworks.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for data science and how your background fits the company's mission. Mention specific projects or experiences that demonstrate your ability to analyse complex datasets and develop machine learning models.
Showcase Your Projects: If you have worked on relevant projects, include them in your application. Highlight any machine learning models you've built, data visualisations you've created, or collaborative efforts with cross-functional teams.
Prepare for Technical Questions: Be ready to discuss your technical skills and experiences during the interview process. Brush up on key concepts in data science, machine learning, and statistical analysis, as well as your familiarity with tools like Tableau or cloud platforms.
How to prepare for a job interview at United Living group
✨Showcase Your Technical Skills
Be prepared to discuss your experience with programming languages like Python, R, or SQL. Bring examples of machine learning models you've built and be ready to explain the techniques you used and the outcomes achieved.
✨Communicate Clearly
Since you'll need to present complex data insights to non-technical stakeholders, practice explaining your findings in simple terms. Use visual aids or examples to illustrate your points during the interview.
✨Demonstrate Collaboration
Highlight your experience working with cross-functional teams. Be ready to share specific examples of how you've collaborated with product managers, engineers, or marketing teams to develop data-driven solutions.
✨Stay Updated on Industry Trends
Research the latest trends in data science and machine learning before your interview. Being knowledgeable about current technologies and methodologies will show your passion for the field and your commitment to continuous learning.
