Senior Applied Scientist, Agentic AI & AI Assistant in London

Senior Applied Scientist, Agentic AI & AI Assistant in London

London Full-Time 63000 - 77000 £ / year (est.) No working from home possible
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At a Glance

  • Tasks: Design and develop cutting-edge agentic AI applications from evaluation to production.
  • Company: Join The Trade Desk's innovative AI Lab, a leader in data-driven advertising.
  • Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
  • Other info: Mentorship opportunities and involvement in large-scale experiments await you.
  • Why this job: Make a real impact in AI while collaborating with top talent in the industry.
  • Qualifications: Experience in applied science, AI applications, and strong collaboration skills.

The predicted salary is between 63000 - 77000 £ per year.

The Trade Desk seeks an experienced Applied Scientist for its AI Lab to design agentic AI applications and own end-to-end components from evaluation to production. You will work on agent safety, evaluation harnesses, and prompt optimization, collaborating with engineering, AI Infrastructure, and Omnichannel teams to push the boundaries of data-driven advertising technologies. You will mentor colleagues, lead large-scale experiments, and contribute to the roadmap while delivering high-impact.

Senior Applied Scientist, Agentic AI & AI Assistant in London employer: The Trade Desk

The Trade Desk is an exceptional employer that fosters a collaborative and innovative work culture, particularly within its AI Lab in a vibrant tech hub. Employees benefit from extensive growth opportunities, mentorship programs, and the chance to lead impactful projects in cutting-edge AI applications, all while contributing to the future of data-driven advertising technologies.

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Contact Details:

The Trade Desk Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Senior Applied Scientist, Agentic AI & AI Assistant 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 The Trade Desk!

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 Senior Applied Scientist, Agentic AI & AI Assistant at The Trade Desk.

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 The Trade Desk.

Apply Directly through Our Website

When you find a suitable opening like Senior Applied Scientist, Agentic AI & AI Assistant at The Trade Desk, 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 Senior Applied Scientist, Agentic AI & AI Assistant in London

Applied Science
AI Application Design
End-to-End Component Ownership
Agent Safety
Evaluation Harnesses
Prompt Optimization
Collaboration Skills

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 The Trade Desk, 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 The Trade Desk. 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 The Trade Desk

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 The Trade Desk!

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.