At a Glance
- Tasks: Use data science to solve strategic business problems and drive impactful decisions.
- Company: Join Google DeepMind, a leader in AI innovation and ethical technology.
- Benefits: Competitive salary, collaborative culture, and exposure to senior leadership.
- Why this job: Make a real impact by translating data into actionable insights for a better world.
- Qualifications: 3+ years in data analysis, strong SQL and Python skills, and excellent communication.
- Other info: Dynamic environment with opportunities for professional growth and mentorship.
The predicted salary is between 36000 - 60000 £ per year.
Are you an experienced Applied Data Scientist (3+ years of experience) excited to use strong technical and analytical skills to power our mission to bring the benefits of AI to the world? Join Google DeepMind’s Core Analytics Team on a Fixed Term Contract! You will bring a data lens to strategic business problems around our People & Culture strategy and research priorities – contributing to Google DeepMind’s mission.
This role focuses on leveraging data science techniques – particularly advanced SQL, Python for analysis, and statistical methods – to drive strategic decisions and generate insights, rather than deep machine learning model development.
The Core Analytics Team (CAT) are a full stack data science team that organise, model, and deploy data to guide Google DeepMind strategy & decisions, blending our technical skillset with rich stakeholder relationships to deliver impact.
We are looking for an experienced Applied Data Scientist who is skilled at and motivated by translating ambiguous business problems into structured, data-driven analyses that drive organisational decisions and change. This role will focus on driving data-driven decision-making in our research planning, and People & Culture teams. You will provide critical insights into areas such as measurement of research impact, investment strategy, attrition and employee engagement.
You will be embedded within the problem domain, working closely with program managers, engineers, the People & Culture team, and leadership to understand their challenges, formulate key questions, and deliver timely insights.
Key responsibilities- Strategic Partnership: Work directly with stakeholders, including senior leaders, to identify, scope, and prioritise high-impact analytical questions.
- Analysis: Conduct rigorous, end-to-end analyses using SQL, Python, and statistical methods to uncover insights, model trends, and answer complex questions about efficiency, usage patterns, and strategic investments.
- Data Storytelling & Communication: Translate complex analytical findings into clear, compelling narratives and actionable recommendations for diverse audiences (technical and non-technical) through presentations, reports, and dashboards.
- Enablement & Monitoring: Develop and maintain tools (dashboards, reports) to provide ongoing visibility into key metrics and empower stakeholders with self-service analytics where appropriate.
- Identify Data Needs: Collaborate with engineering and product teams to highlight data gaps and advocate for the collection of telemetry needed to improve future analyses and decision-making.
- Team Contribution: Share knowledge, contribute to the team's analytical road map, and help improve our overall processes and best practices.
What We Can Offer You:
- Direct Strategic Impact: Your analysis and recommendations will directly inform critical investment and strategic decisions, influencing our ability to achieve our mission.
- Leadership Exposure: Work closely with senior leaders and key decision-makers, honing your communication and influencing skills.
- Collaborative Environment: Be part of a supportive and highly skilled data & analytics group, learning from peers and contributing to a culture of analytical excellence.
About you
We’re looking for an experienced data professional (3+ years of experience as a e.g. Data Scientist, Data Analyst, Quantitative Analyst, Product Data Scientist) with a proven ability to translate complex business or operational challenges into impactful data-driven solutions and strategic recommendations. You thrive on diving deep into data, excel at communicating insights clearly, and are motivated by seeing your analytical insights, developed through close collaboration with partners, directly influence critical decisions.
Analytical Problem Solving: Proven ability to understand ambiguous problems, formulate key questions, and design/execute appropriate analytical approaches.Advanced SQL for Analysis: High proficiency in using SQL to extract, manipulate, aggregate, and analyze complex datasets from various sources to answer business questions.
Stakeholder Management & Communication: Strong track record of building relationships, collaborating effectively, and presenting complex findings and recommendations clearly and persuasively to diverse audiences, including senior leadership. Experience in "data storytelling."
Applied Statistics/Quantitative Skills: Solid understanding and practical application of statistical concepts for analysis (e.g., hypothesis testing, regression, forecasting).
Delivery & Execution: Ability to manage multiple analytical projects simultaneously, prioritise effectively, and deliver high-quality insights in a dynamic environment. You are comfortable working independently and taking ownership.
Useful Skills:
- Domain Interest/Experience: Experience with or a strong interest in research (bibliometrics, innovation pathways/lifecycles, and learning more about key areas/topics in AI research) or People & Culture (HR, recruiting, performance, or employee engagement).
- AI Fluency: Ability and curiosity to use AI tools practically and effectively in your work, with a recognition and awareness of AI’s responsible use, risks, and limitations.
- Python for Data Analysis: Proficiency in Python and common data analysis libraries (e.g., Pandas, NumPy, SciPy, Scikit-learn, Matplotlib/Seaborn).
- Data Visualization/Dashboarding: Experience creating effective dashboards and visualizations using tools like Tableau, Looker, Google Data Studio, or similar.
- Analytics Engineering: Experience designing and implementing ELT workflows (using tools like dagster, dbt).
- Coaching/Mentoring: Experience mentoring others in analytical techniques or tools.
If you don’t think you embody all of the above criteria, please still seriously consider applying! This role (and therefore the requirements) is broad, and we’d be excited to discuss how you see yourself contributing across it.
At Google DeepMind, we value diversity of experience, knowledge, backgrounds and perspectives and harness these qualities to create extraordinary impact. We are committed to equal employment opportunities regardless of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, pregnancy, or related condition (including breastfeeding) or any other basis as protected by applicable law.
Applied Data Scientist - London, UK - FTC employer: Google DeepMind
Contact Detail:
Google DeepMind Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Applied Data Scientist - London, UK - FTC
✨Tip Number 1
Network like a pro! Reach out to people in your field, attend meetups, and connect with professionals on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Prepare for interviews by practising common questions and showcasing your analytical skills. Use real-life examples from your experience to demonstrate how you've tackled complex problems and delivered insights.
✨Tip Number 3
Don’t just apply blindly! Tailor your approach for each role. Research the company, understand their mission, and align your skills with their needs. This shows genuine interest and can set you apart from other candidates.
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Keep an eye on our website for the latest job postings. Applying directly through our site not only streamlines your application but also shows your enthusiasm for joining our team at Google DeepMind!
We think you need these skills to ace Applied Data Scientist - London, UK - FTC
Some tips for your application 🫡
Tailor Your Application: Make sure to customise your CV and cover letter for the Applied Data Scientist role. Highlight your experience with SQL, Python, and data storytelling, as these are key skills we're looking for!
Showcase Your Analytical Skills: Use specific examples from your past work to demonstrate how you've tackled complex business problems with data-driven solutions. We love seeing how you’ve made an impact through your analyses!
Communicate Clearly: Remember, we want to see how well you can translate complex findings into simple narratives. Use clear language in your application to show us your communication skills right from the start.
Apply Through Our Website: Don’t forget to submit your application through our website! It’s the best way for us to receive your details and get the ball rolling on your journey with StudySmarter.
How to prepare for a job interview at Google DeepMind
✨Know Your Data Tools
Make sure you're well-versed in SQL and Python, as these are crucial for the role. Brush up on your skills by working on sample datasets or projects that showcase your ability to extract insights and perform analyses.
✨Understand the Business Context
Before the interview, research Google DeepMind's mission and the specific challenges faced by their Core Analytics Team. This will help you frame your answers in a way that aligns with their strategic goals and demonstrates your understanding of their work.
✨Practice Data Storytelling
Prepare to explain complex analytical findings in simple terms. Think of examples where you've successfully communicated insights to non-technical stakeholders. This will show your ability to translate data into actionable recommendations.
✨Engage with Stakeholders
Be ready to discuss how you've collaborated with different teams in the past. Highlight your experience in building relationships and managing expectations, as this is key for working closely with program managers and leadership at Google DeepMind.