Data Scientist

Data Scientist

Full-Time 30000 - 42000 ÂŁ / year (est.) Home office (partial)
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At a Glance

  • Tasks: Build and deploy innovative AI and ML solutions for diverse clients.
  • Company: Join a fast-growing consultancy dedicated to solving tough challenges with data science.
  • Benefits: Enjoy a competitive salary, 33 days holiday, and professional development opportunities.
  • Why this job: Make a real impact while working on exciting projects across various industries.
  • Qualifications: Experience with Python, SQL, and a passion for data science and machine learning.
  • Other info: Collaborative culture with regular team socials and a commitment to diversity.

The predicted salary is between 30000 - 42000 ÂŁ per year.

The Role in 30 Seconds

Full‑time Data Scientist. Build and deploy cutting‑edge AI and ML solutions for diverse clients (from Government to Startups). Gain full‑stack delivery experience across an array of industries while benefiting from investment in your professional growth and expertise.

Working at Coefficient

You’ll be involved in a wide variety of projects, from cutting‑edge AI solutions for the UK government to building transformative tools across a range of industries. This isn’t just a standard Data Science position; you will gain hands‑on experience by delivering end‑to‑end data science and engineering solutions for our clients, alongside building and improving our own internal products. You can also expect plenty of mentoring and guidance along the way: we aim to be best‑in‑class at what we do, and we want to work with people who share that same attitude. As a unique and fast‑growing consultancy, this is an excellent opportunity to make a significant impact and shape our future success.

About Coefficient

Coefficient is a full‑stack data consultancy dedicated to helping organisations solve their toughest challenges using data science, software engineering, machine learning, analytics, and artificial intelligence.

  • Consulting & Delivery: We partner with clients to deliver end‑to‑end solutions, combining statistical expertise with agile delivery. This might involve developing cutting‑edge models for a UK government agency, or working as an in‑house team with a fast‑growing tech start‑up.
  • Training: Beyond consulting, we create and deliver tailored training programmes via workshops, online learning, and hybrid curriculum to help our clients build their own internal skills. Past clients include BNP Paribas, EY, Hawk‑Eye, the BBC, ACCA, CIOT, and the Metropolitan Police.

We enjoy variety in our work. One week, you might be developing high‑speed trading algorithms; the next, you could be optimising logistics for delivery drivers or building election forecasting models.

Our Team and Culture

Our team is our greatest asset. We invest heavily in professional development through our "10% Time" programme and our annual conference budget. We work with highly intelligent and passionate people who take pride in their work and enjoy a high level of independence.

Our ideal candidate would:

  • Be comfortable using Python and SQL for data analysis, data science, and/or machine learning.
  • Have used any libraries in the Python Open Data Science Stack (e.g. pandas, NumPy, matplotlib, Seaborn, scikit‑learn).
  • Enjoy sharing knowledge, experience, and passion with others.
  • Be passionate about leveraging the latest LLM tooling for accelerated AI‑enhanced delivery without compromising on quality.
  • Have great communication skills. You will be expected to write and contribute towards presentation slide decks to showcase our work during sprint reviews and client project demos.

We recognise that diverse teams are the most successful teams, and we know some people are less likely to apply for the role unless they are 100% qualified. Please do not worry if you don’t meet every single requirement listed. We strongly encourage you to apply if this role excites you and you believe you have the potential to grow here. If you are unsure, please reach out to us - we would genuinely love to hear from you. We are committed to fostering a diverse, inclusive, and empowering culture at Coefficient.

Location and Eligibility Requirements

This is a UK‑based, hybrid role. While we operate remotely for most of the month, we value in‑person collaboration and regularly gather the whole team. The successful candidate must be able to travel to London for on‑site work approximately 2-4 days per month.

Eligibility: You must already have the right to work in the UK. Visa Sponsorship: Please note, we are unable to offer sponsorship for a Skilled Worker visa for this position. Students: We are unable to consider applications from candidates currently in full‑time education (including PhD students).

The Basics

  • Location: We are based in Central London, but we are remote‑friendly. You may be required to work on‑site at clients’ offices.
  • Salary: ÂŁ38,000 annual salary with a meaningful uplift following a performance review at the successful 3‑month probation mark.
  • Holiday: 33 days of annual paid holiday, including bank holidays.
  • Pension: We’re set up with Smart Pension to make sure we’re contributing to help you save for retirement.
  • Performance Reviews: Regular check‑ins to ensure you’re progressing in your career and maximising your potential.
  • Opportunity: To be part of a unique and exciting company that prizes excellence of work. You will work closely with the CEO and become part of a dedicated and forward‑thinking team. We want you to push yourself to learn new skills and be recognised as one of the best in your field.
  • Commitment: We were one of the first 80 signatories of TechZero. We are committed to challenging the status quo and are always looking for ways to make a positive impact.
  • Co‑working Spaces: Regular co‑working days at different locations in London with the team plus full access to the Hubble co‑working network at all times to use a space near where you live.
  • Learning and Professional Development: Potential to improve skills through paid courses and subscriptions. We encourage all our team to engage with professional communities, we actively sponsor PyData Meetups and Humble Data, and we provide additional support for anyone wishing to speak at meetups/conferences.
  • Conference Budget: ÂŁ1000 per employee in year 1, rising to ÂŁ2000 by year 3. This can help cover tickets, accommodation, and travel to attend relevant conferences.
  • Spill: All‑in‑one mental health support programme with on‑demand access to a variety of support. We cover 8 hours of therapy with a remote therapist for each team member every year, worth up to ÂŁ520.
  • Headspace: Paid membership to Headspace to encourage good daily mental practices.
  • 10% Time: 4 hours per week dedicated to improving skills or pursuing your own project.
  • Laptop & Peripherals: Company‑owned Apple laptop plus peripherals such as a monitor and keyboard, for making remote working both comfortable and safe.
  • Team Culture: We have a fantastic small team who enjoy socials together - everything from guided walking tours to escape rooms to Bake Off experiences.

What to expect from the hiring process:

We aim for a transparent, efficient, and enjoyable hiring process. Here is what you can expect:

  • Round 1: Application Screening. We review your application materials (CV, screening questions, and code samples) to assess the initial match. Note: Your application must include answers to the screening questions and code samples to proceed beyond this stage.
  • Round 2: One‑Way Video Interview (Non‑Technical). This is designed for us to get a better sense of your interests and personality outside of your technical skills.
  • Round 3: Practical Coding Exercise (1 hour). You will be booked for a 1‑hour slot to complete a coding test. This exercise is carefully designed to mirror the practical, real‑world data tasks you can expect to do at Coefficient.
  • Round 4: Technical Interview (1 hour). You will meet with a member of our Data Team for a deep dive into the technical skills required for the role. Expect a collaborative session, including pair programming, to see how you approach problems in a team environment.
  • Round 5: Final Conversation with the CEO. This is an opportunity to discuss your motivations, long‑term career goals, and ensure a strong cultural alignment. We want to know that you’ll be a great fit for our team, but we also want to help you achieve your goals.

Our Commitment to You

Speed: We are committed to moving quickly with this role, and you can expect swift feedback after each completed round. Feedback Policy: We are unfortunately unable to offer feedback before Round 2. Feedback for subsequent rounds will always be provided if requested. Please ensure that emails from our hiring platform (Workable) are not being filtered into your spam/junk folder. We want to make sure you receive all correspondence promptly! Due to a large volume of applications, we are unable to consider applicants without code samples and submitted screening questions.

Data Scientist employer: Coefficient

At Coefficient, we pride ourselves on being a forward-thinking consultancy that not only delivers cutting-edge AI and ML solutions but also invests heavily in the professional growth of our team members. With a vibrant work culture that encourages independence, collaboration, and continuous learning, employees enjoy generous benefits such as 33 days of annual leave, a dedicated conference budget, and mental health support, all while working in the dynamic environment of Central London. Join us to make a meaningful impact across diverse industries and be part of a team that values excellence and innovation.
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Contact Detail:

Coefficient Recruiting Team

StudySmarter Expert Advice 🤫

We think this is how you could land Data Scientist

✨Tip Number 1

Get your networking game on! Reach out to people in the industry, attend meetups, and connect with current employees at Coefficient. A friendly chat can sometimes lead to opportunities that aren’t even advertised!

✨Tip Number 2

Prepare for those interviews like a pro! Brush up on your Python and SQL skills, and be ready to showcase your knowledge of data science libraries. Practice coding challenges to get comfortable with the practical tasks you might face.

✨Tip Number 3

Show off your passion! During interviews, share your excitement about AI and machine learning. Talk about projects you've worked on or tools you've used. This will help you stand out as someone who’s genuinely interested in the field.

✨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 serious about joining the Coefficient team. We can’t wait to see what you bring to the table!

We think you need these skills to ace Data Scientist

Python
SQL
Data Analysis
Machine Learning
AI Solutions
Statistical Expertise
Open Data Science Stack (e.g. pandas, NumPy, matplotlib, Seaborn, scikit-learn)
Communication Skills
Presentation Skills
Agile Delivery
End-to-End Data Science Solutions
Mentoring
Problem-Solving Skills
Collaboration

Some tips for your application 🫡

Show Your Passion: When you're writing your application, let your enthusiasm for data science shine through! We want to see that you’re genuinely excited about the role and how you can contribute to our team.

Tailor Your CV: Make sure your CV is tailored to the Data Scientist position. Highlight relevant experience with Python, SQL, and any libraries from the Open Data Science Stack. We love seeing how your skills align with what we do!

Answer Screening Questions Thoughtfully: Don’t rush through the screening questions! Take your time to provide thoughtful answers that reflect your understanding of the role and your problem-solving approach. This is your chance to stand out!

Include Code Samples: Remember to include code samples in your application. We want to see your coding style and how you tackle data challenges. It’s a crucial part of the process, so don’t skip it!

How to prepare for a job interview at Coefficient

✨Know Your Tech Stack

Make sure you're comfortable with Python and SQL, as well as the libraries in the Python Open Data Science Stack like pandas and scikit-learn. Brush up on your coding skills before the practical exercise; practice makes perfect!

✨Showcase Your Projects

Prepare to discuss any relevant projects you've worked on, especially those involving AI or machine learning. Be ready to explain your thought process, the challenges you faced, and how you overcame them. This will demonstrate your hands-on experience.

✨Communicate Clearly

Since you'll need to contribute to presentation slide decks, practice explaining complex concepts in simple terms. Good communication is key, so think about how you can convey your ideas effectively during the interview.

✨Cultural Fit Matters

Coefficient values a strong team culture, so be prepared to discuss your motivations and how you align with their values. Show enthusiasm for collaboration and continuous learning, and don’t hesitate to share your passion for data science!

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