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- Tasks: Analyse text data and build AI-driven solutions to identify real-world entities.
- Company: Join a leading tech firm with a focus on innovation and collaboration.
- Benefits: Competitive salary, flexible working options, and opportunities for professional growth.
- Other info: Fast-paced environment with excellent career advancement opportunities.
- Why this job: Make a real impact by solving complex problems with cutting-edge technology.
- Qualifications: 2+ years of experience with large datasets, SQL, and Python.
The predicted salary is between 50000 - 60000 £ per year.
About the Role
We're looking for a talented Data Scientist ready to take the next step in their career, someone who thrives on analysing text data and is adept at using AI alongside an expansive machine learning toolkit to build high precision solutions to identify real world entities within billions of lines of text data. With access to one of the most comprehensive, market leading, multi-country consumer transaction datasets available, you will expand the merchant vocabulary (named entity recognition), build new models and enhance the accuracy of our existing models that power our world class products and the high impact insights produced by our client enablement and commercial teams.
About You
Passionate about solving real-world problems through a blend of applied data science, analytical thinking and research. Curious with a penchant for accuracy, you love uncovering patterns in text that haven't yet been discovered and can do so without compromising intellectual integrity and accuracy. Product driven thinking enables you to systematise your work into reusable and repeatable processes that can be integrated easily into our data platform. Thrive in a fast‑paced, collaborative environment that values both analytical rigour and commercial impact.
Key Responsibilities
- Contribute to the full ML lifecycle including model training, evaluation, versioning, deployment, and iterative improvement for a suite of text-based classification models.
- Assist in the development of new product concepts.
- Evaluate and validate new data sources for suitability, quality, and bias in ML training pipelines.
- Assist in developing and implementing efficient strategies for creating high‑quality labelled training datasets, leveraging automation, weak supervision, and active learning techniques.
- Design, implement, and maintain rule‑based data processing logic leveraging regex and other pattern‑matching approaches.
- Assist in developing monitoring systems for in‑life machine learning models that automatically detect and flag issues.
- Work with stakeholders to define and implement new machine learning applications based on transaction data.
Essential Skills & Knowledge
- 2+ years' experience working with large datasets.
- Experience in SQL and Python in a professional context.
- Fast learner and comfortable with uncertainty and change; we are a scale‑up.
- Comfortable working with data cleaning, transformation, and basic scripting tasks.
- Knowledge of or experience with developing production code and source control via Git.
- Strong attention to detail and a focus on data quality.
Desirable Skills & Knowledge
- Knowledge of or experience with Spark/Databricks.
- Experience monitoring and enhancing in‑life ML Models (MLOps).
- Familiarity with classification, time series, and/or natural language processing.
- Knowledge of or experience working with consumer data, banking data, or stocks and shares.
- Planning skills to help you prioritise work across multiple projects.
- Familiarity with regex or willingness to learn quickly.
Data Scientist in Hemel Hempstead employer: Fable Data
Contact Detail:
Fable Data Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist in Hemel Hempstead
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect on LinkedIn. 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 projects, especially those involving text data analysis and machine learning. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical skills and understanding the latest trends in data science. Practice explaining your thought process when solving problems, as this will demonstrate your analytical thinking and passion for the field.
✨Tip Number 4
Don’t forget to apply through our website! We love seeing candidates who are genuinely interested in joining our team. Tailor your application to highlight how your experience aligns with our needs, especially in areas like model training and data quality.
We think you need these skills to ace Data Scientist in Hemel Hempstead
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that match the Data Scientist role. Highlight your experience with large datasets, SQL, and Python, and don’t forget to mention any relevant projects or achievements!
Craft a Compelling Cover Letter: Your cover letter is your chance to show us your passion for data science and problem-solving. Share specific examples of how you've tackled real-world problems using data, and let your enthusiasm shine through!
Showcase Your Projects: If you’ve worked on any interesting projects, especially those involving machine learning or text data analysis, make sure to include them in your application. We love seeing practical applications of your skills!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands and shows us you’re serious about joining the StudySmarter team!
How to prepare for a job interview at Fable Data
✨Know Your Data Science Stuff
Make sure you brush up on your data science fundamentals, especially around text data analysis and machine learning. Be ready to discuss your experience with SQL and Python, as well as any projects you've worked on that involved large datasets. This will show your technical prowess and how you can contribute to their team.
✨Showcase Your Problem-Solving Skills
Prepare examples of how you've tackled real-world problems using data science. Think about specific instances where you identified patterns in data or improved model accuracy. This will demonstrate your analytical thinking and passion for solving complex issues, which is key for this role.
✨Familiarise Yourself with Their Products
Take some time to understand the company's products and how they leverage machine learning. Being able to discuss how you can enhance their existing models or contribute to new product concepts will set you apart. It shows you're not just interested in the job, but also in their mission and impact.
✨Ask Insightful Questions
Prepare thoughtful questions about their data sources, model monitoring systems, or the collaborative environment they promote. This not only shows your genuine interest in the role but also gives you a chance to assess if the company aligns with your career goals and values.