At a Glance
- Tasks: Lead project teams to deliver bespoke algorithms and mentor junior data scientists.
- Company: Join Faculty, a leader in human-centric AI consultancy with over 350 global clients.
- Benefits: Enjoy a diverse team, professional growth opportunities, and the chance to work on impactful projects.
- Why this job: Be part of a dynamic culture, learn from experts, and contribute to cutting-edge AI solutions.
- Qualifications: Senior experience in data science, strong Python skills, and leadership mindset required.
- Other info: Opportunities to teach and present at conferences while shaping the future of AI.
The predicted salary is between 48000 - 72000 £ per year.
About Faculty
At Faculty, we transform organisational performance through safe, impactful and human-centric AI.
With a decade of experience, we provide over 300 global customers with software, bespoke AI consultancy, and Fellows from our award winning Fellowship programme.
Our expert team brings together leaders from across government, academia and global tech giants to solve the biggest challenges in applied AI.
Should you join us, you’ll have the chance to work with, and learn from, some of the brilliant minds who are bringing Frontier AI to the frontlines of the world.
We operate a hybrid way of working, meaning that you\’ll split your time across client location, Faculty\’s Old Street office and working from home depending on the needs of the project. For this role, you can expect to be client-side for up-to three days per week at times and working either from home or our Old street office for the rest of your time.What you\’ll be doing:
As a Senior Data Scientist in our Defence business unit you will lead project teams that deliver bespoke algorithms to our clients across the defence and national security sector. You will be responsible for conceiving the data science approach, for designing the associated software architecture, and for ensuring that best practices are followed throughout.
You will help our excellent commercial team build strong relationships with clients, shaping the direction of both current and future projects. Particularly in the initial stages of commercial engagements, you will guide the process of defining the scope of projects to come with an emphasis on technical feasibility. We consider this work as fundamental towards ensuring that Faculty can continue to deliver high-quality software within the allocated timeframes.
You will play an important role in the development of others at Faculty by acting as the designated mentor of a small number of data scientists, and by supporting the professional growth of data scientists on the project team. The latter includes giving targeted support where needed, and providing step-up opportunities where helpful.
Faculty has earned wide recognition as a leader in practical data science. You will actively contribute to the growth of this reputation by delivering courses to high-value clients, by talking at major conferences, by participating in external roundtables, or by contributing to large-scale open-source projects. You will also have the opportunity to teach on the fellowship about topics that range from basic statistics to reinforcement learning, and to mentor the fellows through their 6-week project.
Thanks to Faculty platform, you will have access to powerful computational resources, and you will enjoy the comforts of fast configuration, secure collaboration and easy deployment. Because your work in data science will inform the development of our AI products, you will often collaborate with software engineers and designers from our dedicated product team.
Who we\’re looking for:
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Senior experience in either a professional data science position or a quantitative academic field
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Strong programming skills as evidenced by earlier work in data science or software engineering. Although your programming language of choice (e.g. R, MATLAB or C) is not important, we do require the ability to become a fluent Python programmer in a short timeframe
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An excellent command of the basic libraries for data science (e.g. NumPy, Pandas, Scikit-Learn) and familiarity with a deep-learning framework (e.g. TensorFlow, PyTorch, Caffe)
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A high level of mathematical competence and proficiency in statistics
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A solid grasp of essentially all of the standard data science techniques, for example, supervised/unsupervised machine learning, model cross validation, Bayesian inference, time-series analysis, simple NLP, effective SQL database querying, or using/writing simple APIs for models. We regard the ability to develop new algorithms when an innovative solution is needed as a fundamental skill
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A leadership mindset focussed on growing the technical capabilities of the team; a caring attitude towards the personal and professional development of other data scientists; enthusiasm for nurturing a collaborative and dynamic culture
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An appreciation for the scientific method as applied to the commercial world; a talent for converting business problems into a mathematical framework; resourcefulness in overcoming difficulties through creativity and commitment; a rigorous mindset in evaluating the performance and impact of models upon deployment
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Some commercial experience, particularly if this involved client-facing work or project management; eagerness to work alongside our clients; business awareness and an ability to gauge the commercial value of projects; outstanding written and verbal communication skills; persuasiveness when presenting to a large or important audience
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Experience leading a team of data scientists (to deliver innovative work according to a strict timeline) as well as experience in composing a project plan, in assessing its technical feasibility, and in estimating the time to delivery
What we can offer you:
The Faculty team is diverse and distinctive, and we all come from different personal, professional and organisational backgrounds. We all have one thing in common: we are driven by a deep intellectual curiosity that powers us forward each day.
Faculty is the professional challenge of a lifetime. You’ll be surrounded by an impressive group of brilliant minds working to achieve our collective goals.
Our consultants, product developers, business development specialists, operations professionals and more all bring something unique to Faculty, and you’ll learn something new from everyone you meet.
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Senior Data Scientist employer: Faculty
Contact Detail:
Faculty Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Scientist
✨Tip Number 1
Familiarise yourself with Faculty's core values and mission. Understanding their focus on human-centric AI and organisational performance will help you align your experiences and skills with what they value most in a Senior Data Scientist.
✨Tip Number 2
Network with current or former employees of Faculty, especially those in data science roles. Engaging in conversations about their experiences can provide insights into the company culture and expectations, which can be invaluable during interviews.
✨Tip Number 3
Stay updated on the latest trends and advancements in applied AI and data science. Being able to discuss recent developments or case studies during your interactions with Faculty will demonstrate your passion and commitment to the field.
✨Tip Number 4
Prepare to showcase your leadership skills and mentoring experience. Since the role involves guiding other data scientists, think of specific examples where you've successfully led a team or supported the professional growth of others.
We think you need these skills to ace Senior Data Scientist
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in data science and showcases your strong Python programming skills. Include specific projects where you've used libraries like NumPy, Pandas, and Scikit-Learn.
Craft a Compelling Cover Letter: In your cover letter, express your passion for AI and how your leadership mindset aligns with Faculty's values. Mention your experience in client-facing roles and your ability to convert business problems into mathematical frameworks.
Showcase Your Technical Skills: Clearly outline your proficiency in data science techniques and tools. Highlight any experience with deep learning frameworks like TensorFlow or PyTorch, and provide examples of how you've applied these skills in previous roles.
Demonstrate Your Mentorship Experience: If you have experience mentoring other data scientists, be sure to include this in your application. Discuss how you've supported their professional growth and contributed to a collaborative team culture.
How to prepare for a job interview at Faculty
✨Showcase Your Technical Skills
As a Senior Data Scientist, you'll need to demonstrate your strong Python programming skills and familiarity with data science libraries. Be prepared to discuss specific projects where you've used tools like NumPy, Pandas, or TensorFlow, and how you approached problem-solving in those scenarios.
✨Emphasise Leadership Experience
Highlight your experience in leading teams and mentoring junior data scientists. Faculty values a leadership mindset, so share examples of how you've nurtured a collaborative culture and supported the professional growth of others in your previous roles.
✨Understand the Business Context
Demonstrate your ability to convert business problems into mathematical frameworks. Be ready to discuss how you've assessed the commercial value of projects and your experience in client-facing roles, as this will be crucial for building strong relationships with Faculty's clients.
✨Prepare for Technical Discussions
Expect to engage in technical discussions about data science techniques and methodologies. Brush up on topics like supervised/unsupervised learning, Bayesian inference, and model evaluation, as well as be ready to explain your thought process when designing software architecture for data science projects.