At a Glance
- Tasks: Lead impactful AI projects and mentor junior data scientists.
- Company: Join a pioneering AI company transforming global performance.
- Benefits: Competitive salary, flexible hours, and opportunities for professional growth.
- Other info: Diverse team culture with a commitment to innovation and excellence.
- Why this job: Shape the future of AI while making a positive impact on society.
- Qualifications: Senior experience in data science and strong programming skills in Python.
The predicted salary is between 63000 - 77000 £ per year.
We established Faculty in 2014 because we thought that AI would be the most important technology of our time.
Since then, we've worked with over 350 global customers to transform their performance through human-centric AI.
We innovate, build and deploy responsible AI which moves the needle - and we know a thing or two about doing it well.
We bring an unparalleled depth of technical, product and delivery expertise to our clients who span government, finance, retail, energy, life sciences and defence.
Our business, and reputation, is growing fast and we're always on the lookout for individuals who share our intellectual curiosity and desire to build a positive legacy through technology.
AI is an epoch-defining technology, join a company where you'll be empowered to envision its most powerful applications, and to make them happen.
About the team Our Public Services Business Unit is committed to leveraging AI for the benefit of individual citizens and the public good.
From our work informing strategic government decisions, to optimising our NHS, through to reducing bureaucratic backlogs - we know that AI offers opportunities to drive improvements at every level of Government and we are proud to lead on some of the most impactful work happening in the sector.
Because of the nature of the work we do with our Government clients, you may need to be eligible for UK Security Clearance (SC) and willing to work on site with these clients from time to time.
About the role As a Senior Data Scientist, you will lead high-impact AI projects and shape the technical direction of bespoke solutions.
You will define data science approaches, design robust software architectures, mentor junior colleagues, and ensure delivery rigour across projects all while building deep client relationships and solidifying our reputation as a leader in practical, measurable AI.#Leading project teams that deliver bespoke algorithms and high-stakes AI solutions to clients across the sector.
Conceiving the core data science approach and designing the associated robust software architecture for new engagements.
Mentoring a small number of data scientists and supporting the professional growth of technical team members on projects.
Partnering with commercial teams to build client relationships and shape project scope for technical feasibility.
Contributing to Faculty's thought leadership and reputation through delivering courses, public speaking, or open-source projects.
Ensuring best practices are followed throughout the project lifecycle to guarantee high-quality, impactful delivery.
You possess senior experience in a professional data science position or a quantitative academic field.
You demonstrate strong programming skills, with the ability to be a fluent Python programmer, using core libraries (Num Py, Pandas) and a deep-learning framework (e. g., You have a deep expertise in core data science paradigms (supervised/unsupervised, NLP, validation), demonstrating a proficiency across the standard data science toolkit, including the ability to develop new, innovative algorithms.
You exhibit commercial awareness, with experience in client-facing work and the ability to translate business problems into a rigorous mathematical framework.
You are skilled in project planning, assessing technical feasibility, estimating delivery timelines, and leading a team to deliver high-quality work on a strict schedule.
Our Interview Process Talent Team Screen (30 minutes)Take Home Technical Assessment Technical Interview (90 minutes)Commercial Interview (60 minutes)Our Recruitment Ethos We aim to grow the best team - not the most similar one.
We know that diversity of individuals fosters diversity of thought, and that strengthens our principle of seeking truth.
We are open to conversations about part-time hours.
A note on AI: we're happy for you to use it for research and interview prep, but please don't use it to generate answers during live interviews.
We also use an AI note-taker (Metaview) in interviews so interviewers can stay present (which you can opt out of just let us know,) and every application is reviewed by a human, never decided by AI.
Lead ML / Data Scientist in London employer: Faculty
At Faculty, we pride ourselves on being an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration. As the Head of Banking AI Transformation, you will have the opportunity to lead transformative projects in a rapidly evolving sector while benefiting from our commitment to employee growth through continuous learning and development. Located in a vibrant area, our team enjoys a supportive environment that values diversity and encourages meaningful contributions to the financial services landscape.
StudySmarter Expert Advice🤫
We think this is how you could land Lead ML / Data Scientist 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 Faculty!
✨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 Lead ML / Data Scientist at Faculty.
✨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 Faculty.
✨Apply Directly through Our Website
When you find a suitable opening like Lead ML / Data Scientist at Faculty, 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 Lead ML / Data Scientist 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 Faculty, 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 Faculty. 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 Faculty
✨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 Faculty!
✨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.
