Data Scientist

Data Scientist

London Full-Time 36000 - 60000 £ / year (est.) No home office possible
Faculty

At a Glance

  • Tasks: Design and deploy data science solutions for urgent low-carbon challenges.
  • Company: Join Faculty, a leader in impactful AI consultancy with a diverse team.
  • Benefits: Enjoy continuous learning, mentorship, and the chance to make a real-world impact.
  • Other info: Bonus skills include experience in NLP, deep learning, and customer-facing roles.
  • Why this job: Work on high-impact projects and collaborate with brilliant minds in AI.
  • Qualifications: Strong foundations in data science, programming skills, and a creative problem-solving mindset required.

The predicted salary is between 36000 - 60000 £ per year.

About Faculty

At Faculty, we transform organisational performance through safe, impactful and human-centric AI.

With more than a decade of experience, we provide over 350 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 Data Scientist in our Defence business unit you will be part of project teams that deliver bespoke algorithms to our clients across the Defence 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.

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:

  • Proven experience in either a professional data science position or a quantitative academic field
  • 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 require the ability to become a fluent Python programmer in a short timeframe
  • 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)
  • A high level of mathematical competence and proficiency in statistics
  • 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
  • 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
  • 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
  • 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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Data Scientist employer: Faculty

At Faculty, we pride ourselves on being an exceptional employer, offering a dynamic work culture that fosters continuous learning and professional growth. As a Data Scientist in our Energy Transition & Environment team, you'll engage in impactful projects that address urgent challenges in the low-carbon transition, all while collaborating with a diverse group of talented individuals who share a passion for AI. With opportunities to shape a high-growth business and make a tangible difference, Faculty is the perfect place for those seeking meaningful and rewarding employment.
Faculty

Contact Detail:

Faculty Recruiting Team

StudySmarter Expert Advice 🤫

We think this is how you could land Data Scientist

✨Tip Number 1

Familiarise yourself with the latest trends in AI and data science, especially those related to the energy sector. This will not only help you understand the challenges Faculty is tackling but also allow you to engage in meaningful conversations during interviews.

✨Tip Number 2

Network with professionals in the field by attending industry events or joining relevant online communities. Engaging with others who work in AI and data science can provide insights into the role and may even lead to referrals.

✨Tip Number 3

Prepare to discuss your previous projects in detail, particularly those that involved machine learning or data manipulation. Be ready to explain your thought process, the challenges you faced, and how you overcame them, as this will demonstrate your problem-solving skills.

✨Tip Number 4

Showcase your communication skills by practising how to explain complex technical concepts in simple terms. This is crucial for a role that requires collaboration with both technical and non-technical stakeholders.

We think you need these skills to ace Data Scientist

Data Science Foundations
Machine Learning Techniques
Statistical Analysis
Bayesian Modelling
Time-Series Forecasting
Programming in Python
Data Manipulation with NumPy and Pandas
Communication Skills
Problem-Solving Mindset
Collaboration with Multidisciplinary Teams
Adaptability to Challenges
Presentation Skills for Stakeholders
Knowledge of Statistics and Probability
Experience with MLOps Tooling
Understanding of the Energy Sector

Some tips for your application 🫡

Tailor Your CV: Make sure your CV highlights relevant experience in data science, particularly any projects or roles that involved AI, machine learning, or the energy sector. Use keywords from the job description to demonstrate your fit for the role.

Craft a Compelling Cover Letter: In your cover letter, express your passion for AI and the energy sector. Discuss specific projects or experiences that showcase your problem-solving skills and ability to communicate complex concepts to diverse audiences.

Showcase Technical Skills: Clearly outline your programming experience, especially in Python or other relevant languages. Mention any familiarity with data manipulation libraries like NumPy and Pandas, as well as your understanding of machine learning algorithms.

Demonstrate Curiosity and Learning: Highlight any continuous learning efforts, such as courses or certifications related to data science or AI. This shows your commitment to professional growth and aligns with Faculty's culture of mentorship and development.

How to prepare for a job interview at Faculty

✨Showcase Your Technical Skills

Be prepared to discuss your programming experience, especially in Python. Highlight any projects where you've applied machine learning techniques or data manipulation libraries like NumPy and Pandas.

✨Demonstrate Problem-Solving Abilities

Think of examples where you've turned complex problems into data science solutions. Be ready to explain your thought process and how you approached these challenges, particularly in the context of energy or environmental issues.

✨Communicate Clearly

Practice explaining technical concepts in simple terms. Faculty values clear communication, so be prepared to present your work confidently to both technical and non-technical audiences.

✨Express Curiosity About the Energy Sector

Show your enthusiasm for the energy transition and low-carbon initiatives. Discuss any relevant research or projects you've been involved in that relate to this field, demonstrating your genuine interest in making an impact.

Data Scientist
Faculty
Location: London

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