At a Glance
- Tasks: Join our team to develop and deploy innovative AI/ML models.
- Company: Dynamic tech company in Nine Elms, London with a focus on data-driven solutions.
- Benefits: Competitive salary, 25 days holiday, private health insurance, and cycle to work scheme.
- Other info: Exciting start-up environment with opportunities for growth and collaboration.
- Why this job: Make an impact by leveraging data and working on cutting-edge technologies.
- Qualifications: 1-2 years experience as a Data Scientist and strong Python skills.
The predicted salary is between 50000 - 60000 £ per year.
Location: Nine Elms, London - Full-time
As part of our vision, we are seeking a talented Data Scientist to join our dynamic, expanding team. Over the last few years we’ve built a solid data foundation using best in class technologies (dbt, BigQuery, Airflow) and are just at the start of our journey to leverage this data in a more sophisticated way.
Key Responsibilities
- Stakeholder Management: Help business leaders at Zapp understand and prioritise opportunities related to AI/ML
- End-to-End Development and Ownership: Own the lifecycle of new models from concept to deployment and monitoring, and continuously iterate.
- Reporting/Dashboarding Collaboration: Work closely with cross-functional teams to define, design, and implement new features, driving both business and technical excellence.
- Code Quality: Write scalable, maintainable, and high-quality code while adhering to best practices for testing, deployment, and version control.
Essential Skills
- Minimum of 1-2 years of professional experience as a Data Scientist in a commercial setting.
- Bachelor’s degree in Computer Science, Software Engineering, Mathematics, Physics, or a related field.
- Expertise in Python and developing high-quality, scalable code, hands-on experience with cloud platforms like GCP, AWS, or Azure.
- Solid understanding of SQL.
- Familiarity with version control (Git) and automated deployment pipelines (CI/CD).
Desirable Skills
- Experience with GCP/Vertex AI.
- Past work in retail demand forecasting.
- Experience working in a start-up environment.
Benefits
- Competitive salary.
- Enjoy 25 days of holiday per year (plus all bank holidays).
- Private Health Insurance.
- Extended sick pay and maternity/paternity leave pay.
- Cycle to work scheme.
Data Scientist employer: Zapp
At Zapp, we pride ourselves on being an excellent employer, offering a vibrant work culture in the heart of Nine Elms, London. Our commitment to employee growth is evident through our investment in cutting-edge technologies and collaborative projects that empower our Data Scientists to take ownership of their work while enjoying competitive benefits such as private health insurance and generous holiday allowances. Join us to be part of a forward-thinking team where your contributions will directly impact our journey towards leveraging data for innovative solutions.
StudySmarter Expert Advice🤫
We think this is how you could land Data Scientist
✨Get Involved in Data Science Meetups
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✨Show Off Your Projects
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Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Zapp.
✨Apply Directly through Our Website
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We think you need these skills to ace Data Scientist
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Zapp, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Zapp. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Zapp
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Zapp!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
