At a Glance
- Tasks: Develop scalable backend systems using Python and FastAPI for an innovative intelligence platform.
- Company: Join a dynamic global team in Greater London with a startup vibe and enterprise resources.
- Benefits: Enjoy competitive pay, flexible work options, and opportunities for professional growth.
- Other info: Be part of a collaborative environment that fosters innovation and career advancement.
- Why this job: Make a real impact on media efficiency through cutting-edge AI technology.
- Qualifications: 3+ years in backend engineering with strong skills in Python, FastAPI, and cloud services.
The predicted salary is between 50000 - 70000 £ per year.
Global is seeking a mid-level AI Engineer specializing in Python for their Global:IQ team in Greater London. This role involves backend engineering to develop scalable systems integral to their new intelligence platform, which harnesses data science and AI methodologies.
Successful candidates will require:
- 3+ years of experience in backend engineering
- Proficiency in Python, FastAPI, and Postgres
- Experience with cloud services like AWS
- Experience with data warehousing solutions such as Snowflake
The position offers a blend of startup culture with enterprise resources, ideal for those looking to impact media efficiency through innovative technology.
Python AI Backend Engineer (FastAPI + Snowflake) in London employer: Global
Global is an exceptional employer that fosters a dynamic work culture, blending the agility of a startup with the robust resources of an enterprise. Employees benefit from a collaborative environment that encourages innovation and personal growth, alongside opportunities to work on cutting-edge technology that significantly enhances media efficiency. Located in Greater London, the company offers competitive benefits and a commitment to professional development, making it an ideal place for those seeking meaningful and rewarding careers in AI engineering.
StudySmarter Expert Advice🤫
We think this is how you could land Python AI Backend Engineer (FastAPI + Snowflake) in 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 Global!
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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 Python AI Backend Engineer (FastAPI + Snowflake) at Global.
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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 Global.
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When you find a suitable opening like Python AI Backend Engineer (FastAPI + Snowflake) at Global, 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 Python AI Backend Engineer (FastAPI + Snowflake) in 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 Global, 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 Global. 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 Global
✨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 Global!
✨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.
