At a Glance
- Tasks: Own the end-to-end data wrangling process for large financial datasets.
- Company: Exciting London-based startup with a focus on innovation.
- Benefits: Competitive salary, equity options, and a vibrant office environment.
- Other info: Join a small, dynamic team and grow your career in a fast-paced environment.
- Why this job: Make a real impact by shaping data that drives major financial decisions.
- Qualifications: 3-5 years of experience in building data pipelines or ML systems.
The predicted salary is between 63000 - 77000 £ per year.
Arctal, a London-based startup, is seeking a full-time in-office data engineer to own data wrangling end-to-end: ingestion, cleanup, storage, transformation and distribution of large financial datasets from PDFs.
You'll architect a scalable data pipeline, integrate AI agents, and ensure data quality so that datasets inform millions of dollars in decisions.
3–5 years building data pipelines or ML systems preferred; you’ll ship in a small team.
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AI Data Infrastructure Engineer | Equity & On-site London employer: Arctal
Arctal is an exceptional employer for Data Infrastructure Engineers, offering a dynamic work environment in the heart of London. With a focus on employee growth and autonomy, team members are encouraged to innovate and automate their roles, ensuring that every day presents new challenges and learning opportunities. The competitive salary, meaningful equity, and a fast-paced, collaborative culture make Arctal a standout choice for those looking to make a significant impact in the AI and data infrastructure space.
StudySmarter Expert Advice🤫
We think this is how you could land AI Data Infrastructure Engineer | Equity & On-site London
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Arctal!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like AI Data Infrastructure Engineer | Equity & On-site London at Arctal.
✨Leverage Professional Networks
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 Arctal.
✨Apply Directly through Our Website
When you find a suitable opening like AI Data Infrastructure Engineer | Equity & On-site London at Arctal, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace AI Data Infrastructure Engineer | Equity & On-site London
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 Arctal, 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 Arctal. 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 Arctal
✨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 Arctal!
✨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.
