Senior Intelligence Analyst, Online Safety & Risk in London

Senior Intelligence Analyst, Online Safety & Risk in London

London Full-Time 49500 - 60500 £ / year (est.) No working from home possible
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At a Glance

  • Tasks: Analyse content risks and investigate emerging threats to keep YouTube safe.
  • Company: Join YouTube's dynamic Intelligence and Scaled Insights team.
  • Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
  • Other info: Be part of a mission-driven team focused on innovative solutions.
  • Why this job: Make a real impact on online safety for billions of users.
  • Qualifications: Strong analytical skills and expertise in risk assessment.

The predicted salary is between 49500 - 60500 £ per year.

You Tube’s Intelligence and Scaled Insights team analyzes content risks across social media to inform critical decision-making, keeping You Tube safe for billions of users.

Resourceful and deeply rooted in subject matter expertise and evidence-based analysis, our work spans high-level intelligence to granular investigations.

Within our Intelligence Desk, we identify and investigate emerging threats, uncovering the root causes behind platform risks to help design effective, long-term mitigations.

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Senior Intelligence Analyst, Online Safety & Risk in London employer: Google

As a Senior Manager in Ads Solutions Engineering at gTech, you will thrive in a dynamic and innovative environment that prioritises collaboration and professional growth. The company fosters a culture of continuous learning and development, offering ample opportunities to lead transformative projects while working with cutting-edge technologies. Located in a vibrant tech hub, gTech provides a unique chance to engage with top-tier clients and contribute to impactful solutions that drive success.

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Contact Details:

Google Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Senior Intelligence Analyst, Online Safety & Risk 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 Google!

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 Intelligence Analyst, Online Safety & Risk at Google.

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 Google.

Apply Directly through Our Website

When you find a suitable opening like Senior Intelligence Analyst, Online Safety & Risk at Google, 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 Intelligence Analyst, Online Safety & Risk in London

Analytical Skills
Evidence-Based Analysis
Risk Assessment
Investigative Skills
Threat Identification
Root Cause Analysis
Decision-Making

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 Google, 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 Google. 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 Google

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 Google!

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.