Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Build data-driven solutions and develop machine learning models to support analytics initiatives.
- Company: Join a forward-thinking company at the forefront of data science and AI.
- Benefits: Competitive salary, flexible working hours, and opportunities for professional growth.
- Why this job: Make an impact with cutting-edge technology and innovative data solutions.
- Qualifications: Experience in Python, data analysis, and machine learning concepts required.
- Other info: Dynamic team environment with excellent career advancement opportunities.
The predicted salary is between 28800 - 48000 £ per year.
We are looking for a Data Scientist who can build data-driven solutions, develop machine learning models, and support analytics initiatives. The role requires strong expertise in data analysis, data pipelines, and statistical modeling, with exposure to AI and generative AI technologies as part of modern data solutions.
Key Responsibilities
- Data Engineering & Data Pipelines
- Design, develop, and maintain automated data pipelines using Python and ETL tools.
- Collect, clean, and transform data from multiple sources including APIs, databases, and web scraping.
- Manage and optimize SQL and NoSQL databases to ensure reliable and high-quality datasets.
- Implement data validation, monitoring, and documentation for datasets.
- Data Science & Machine Learning
- Develop and deploy machine learning models for regression, classification, and clustering.
- Perform exploratory data analysis (EDA) to identify trends and insights.
- Apply statistical techniques and model evaluation methods to improve model performance.
- Support experimentation and data-driven decision-making.
- AI & Advanced Analytics (Supporting Role)
- Apply AI and NLP techniques to enhance data-driven products and analytics solutions.
- Work with pre-trained models and frameworks to build intelligent features and insights.
- Support basic use cases involving generative AI, such as information retrieval, text analysis, or automation.
- Analytics & Visualization
- Build dashboards and reports using BI tools such as Tableau, Power BI, or Looker Studio.
- Translate technical findings into clear insights for business stakeholders.
- Collaboration & Delivery
- Work closely with engineering, product, and business teams to deliver data solutions.
- Contribute to backend logic and API integrations when required.
- Follow best practices in version control, documentation, and agile development.
Required Skills & Qualifications
- Core Skills
- Strong proficiency in Python and data science libraries (Pandas, NumPy, Scikit-learn).
- Solid understanding of machine learning concepts and statistical analysis.
- Experience with SQL and data modeling; exposure to NoSQL databases is a plus.
- Experience with ETL pipelines, data integration, and data warehousing concepts.
- Experience with data visualization tools (Tableau, Power BI, etc.).
- AI Exposure (Preferred, Not Mandatory)
- Exposure to deep learning, or generative AI concepts and tools.
- Familiarity with frameworks such as TensorFlow, PyTorch, or Lang Chain is an advantage.
- Tools & Platforms
- Familiarity with cloud platforms (GCP, AWS, or Azure).
- Experience with Docker, Linux, APIs, and Git is a plus.
- Education & Experience
- Bachelor’s degree in computer science, Data Science, Engineering, or related fields.
- Minimum 2 years of experience in data science, analytics, or related roles.
- Soft Skills
- Strong analytical and problem-solving skills.
- Good communication and stakeholder management abilities.
- Ability to work in a fast-paced environment and learn new technologies quickly.
Data Specialist in Penarth employer: ELLIOTT MOSS CONSULTING PTE. LTD.
Contact Detail:
ELLIOTT MOSS CONSULTING PTE. LTD. Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Specialist in Penarth
✨Network Like a Pro
Get out there and connect with people in the industry! Attend meetups, webinars, or even just grab a coffee with someone who works in data. You never know when a casual chat could lead to your next big opportunity.
✨Show Off Your Skills
Create a portfolio showcasing your projects, especially those involving Python, machine learning, or data visualisation. Having tangible examples of your work can really set you apart from the crowd when you're chatting with potential employers.
✨Ace the Interview
Prepare for common data-related interview questions and be ready to discuss your past experiences. Practice explaining complex concepts in simple terms, as this shows you can communicate effectively with non-technical stakeholders.
✨Apply Through Our Website
Don't forget to check out our job listings on the StudySmarter website! Applying directly through us not only makes it easier for you but also helps us keep track of your application and get back to you faster.
We think you need these skills to ace Data Specialist in Penarth
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Data Specialist role. Highlight your experience with data pipelines, machine learning, and any relevant tools like Python and SQL. We want to see how your skills match what we're looking for!
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 your background makes you a great fit for our team. Keep it engaging and personal – we love to see your personality!
Showcase Your Projects: If you've worked on any cool data projects, make sure to mention them! Whether it's a machine learning model or a data visualisation dashboard, we want to see what you've done. Include links if possible – we love seeing your work in action!
Apply Through Our Website: Don't forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it’s super easy – just follow the prompts and you’ll be all set!
How to prepare for a job interview at ELLIOTT MOSS CONSULTING PTE. LTD.
✨Know Your Data Tools
Make sure you brush up on your Python skills and get familiar with libraries like Pandas and NumPy. Be ready to discuss how you've used these tools in past projects, especially when it comes to building data pipelines or machine learning models.
✨Showcase Your Problem-Solving Skills
Prepare to share specific examples of how you've tackled complex data challenges. Think about times when you had to clean messy datasets or optimise SQL queries, and be ready to explain your thought process and the impact of your solutions.
✨Understand AI and Machine Learning Concepts
Even if you don't have extensive experience with generative AI, it's important to show that you understand the basics. Brush up on key concepts and be prepared to discuss how they can be applied in real-world scenarios, especially in relation to the role.
✨Communicate Clearly
Practice translating technical jargon into layman's terms. You'll likely need to explain your findings to non-technical stakeholders, so being able to communicate insights clearly is crucial. Consider preparing a few examples of how you've done this in the past.
