At a Glance
- Tasks: Lead high-impact AI projects and mentor junior data scientists.
- Company: Join Faculty, a leader in responsible AI with a collaborative culture.
- Benefits: Enjoy unlimited annual leave, private healthcare, and flexible working options.
- Why this job: Shape the future of AI while making a real-world impact.
- Qualifications: Senior experience in data science and strong Python programming skills required.
- Other info: Diverse team environment with excellent career growth opportunities.
The predicted salary is between 48000 - 84000 ÂŁ 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 don’t chase hype cycles. 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 Defence team is focused on building and embedding human‑centered AI solutions which give our nation a competitive edge in the defence sector. We collaborate with our clients to bring ethical, reliable and cutting‑edge AI to high‑stakes situations and maintain the balance of global powers essential to our liberty.
Because of the nature of the work we do with our Defence clients, you will need to be eligible for UK Security Clearance (SC) and willing to work between 2 to 4 days per week on‑site with these customers which may require travel to locations throughout the UK. When not required on client sites, you’ll have the flexibility to work from our London office or remotely from elsewhere within the UK.
As a Senior Machine Learning Scientist, you will lead high‑impact AI projects and shape the technical direction of bespoke solutions. This role requires hands‑on technical excellence combined with crucial team leadership. 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.
What you’ll be doing:
- Mapping the end‑to‑end data science approach and designing the associated software 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.
Who we’re looking for:
- 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 (NumPy, Pandas) and a deep‑learning framework (e.g., PyTorch).
- 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 bring a leadership mindset, focused on growing the technical capabilities of the team and nurturing a collaborative culture.
- 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.
The Interview Process:
- Talent Team Screen (30 minutes)
- Take Home Technical Test
- 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. And we know from experience that diverse teams deliver better work, relevant to the world in which we live. We’re united by a deep intellectual curiosity and desire to use our abilities for measurable positive impact. We strongly encourage applications from people of all backgrounds, ethnicities, genders, religions and sexual orientations.
Some of our standout benefits:
- Unlimited Annual Leave Policy
- Private healthcare and dental
- Enhanced parental leave
- Family‑Friendly Flexibility & Flexible working
- Sanctus Coaching
- Hybrid Working (2 days in our Old Street office, London)
If you don’t feel you meet all the requirements, but are excited by the role and know you bring some key strengths, please do apply or reach out to our Talent Acquisition team for a confidential chat – talent@faculty.ai. Please know we are open to conversations about part‑time roles or condensed hours.
Senior Machine Learning Scientist employer: Faculty
Contact Detail:
Faculty Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Machine Learning Scientist
✨Tip Number 1
Network like a pro! Reach out to people in the AI and machine learning space, especially those who work at Faculty or similar companies. A friendly chat can open doors and give you insights that might just help you land that interview.
✨Tip Number 2
Prepare for your interviews by brushing up on your technical skills. Make sure you're comfortable with Python and the core libraries mentioned in the job description. Practising coding challenges can really boost your confidence and show off your expertise.
✨Tip Number 3
Showcase your leadership skills! Be ready to discuss how you've mentored others or led projects in the past. Faculty values collaboration and growth, so highlighting these experiences will make you stand out.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you’re genuinely interested in joining our team and contributing to the exciting work we do in AI.
We think you need these skills to ace Senior Machine Learning Scientist
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that align with the Senior Machine Learning Scientist role. Highlight your programming prowess, especially in Python, and any leadership experience you've had in data science projects.
Craft a Compelling Cover Letter: Use your cover letter to tell us why you're passionate about AI and how your background makes you a great fit for our Defence team. Share specific examples of past projects where you've made an impact, and don’t forget to show off your commercial awareness!
Showcase Your Technical Skills: In your application, be sure to mention your expertise in core data science paradigms and any innovative algorithms you've developed. We love seeing candidates who can demonstrate their technical excellence through real-world applications.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows us you’re keen on joining our team at Faculty!
How to prepare for a job interview at Faculty
✨Know Your AI Stuff
Make sure you brush up on your machine learning concepts and algorithms. Be ready to discuss your experience with Python, NumPy, Pandas, and any deep-learning frameworks like PyTorch. They’ll want to see that you can not only talk the talk but also walk the walk when it comes to technical skills.
✨Showcase Your Leadership Skills
As a Senior Machine Learning Scientist, you'll be expected to lead teams and mentor junior colleagues. Prepare examples of how you've successfully led projects or supported team members in the past. Highlight your ability to foster a collaborative culture and grow technical capabilities within a team.
✨Understand the Business Side
This role requires a blend of technical expertise and commercial awareness. Be ready to discuss how you've translated business problems into data science solutions. Think about specific projects where you’ve partnered with clients and how you shaped project scopes based on technical feasibility.
✨Prepare for Different Interview Stages
The interview process includes a talent team screen, a take-home technical test, and both technical and commercial interviews. Familiarise yourself with each stage and prepare accordingly. Practice coding challenges for the technical test and think about how to articulate your thought process during the interviews.