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.
- Other info: Dynamic environment with opportunities for professional growth and mentorship.
- 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.
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
At Google DeepMind, we pride ourselves on being an exceptional employer, offering a collaborative environment where your analytical insights can directly influence strategic decisions. Our commitment to employee growth is evident through opportunities for leadership exposure and continuous learning within a highly skilled analytics team. Located in London, you will be part of a mission-driven organisation that values diversity and fosters a culture of innovation and ethical AI development.
StudySmarter Expert Advice🤫
We think this is how you could land Applied Data Scientist - London, UK - FTC
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We think you need these skills to ace Applied Data Scientist - London, UK - FTC
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 DeepMind, 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 DeepMind. 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 DeepMind
✨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 DeepMind!
✨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.
