Full Stack Software Engineer
CoefficientLondona month ago
We are looking for a Full Stack Software Engineer to join the Coefficient team full-time. You’ll be working on projects with multiple clients across different industries, from financial services to healthcare to app startups and beyond. You’ll be expected to take ideas from whiteboard to deployment, and to ensure the code we deliver continues to meet the high standards our clients have come to expect from Coefficient.
This is no ordinary software engineering role. You will also be delivering Python workshops, mentoring junior developers and taking a lead on some of our own product ideas. We aim to be best-in-class at what we do, and we want to work with people who share that same attitude.
🚀 Coefficient is a data consultancy offering data science, engineering, machine learning, and other AI-related services, as well as bespoke training courses.
🔎 We are motivated by the commitment of solving real-world problems by combining statistical techniques with a lean start-up mentality and a technical skill set.
🌍 We have designed and delivered data training courses for clients such as BNP Paribas, EY, Hawk-Eye, the BBC, and the Metropolitan Police. Our consulting work is highly multidisciplinary; in a single week we may be writing trading algorithms, routing delivery drivers, and predicting elections.
👥 Our team is our greatest asset, as such we invest heavily in professional development. We work with highly intelligent and passionate people who take pride in their work and enjoy a high level of trust.
You must have the following…
- You must be fluent in Python with considerable experience working with Django in a production environment.
- Passion for good design! You take pride in crafting elegant user interfaces and seamless UX.
You may be a great fit for this role if you also meet any of the following…
- Have good communication skills - this is a client-facing role, so the ability to communicate patiently with clients and to explain processes in clear and simple language is important.
- Have some experience of using libraries in the Python Open Data Science Stack, especially using pandas for working with data.
- Have used MySQL/MariaDB, PostgresSQL, Oracle and MSSQL or similar and you know your way around a production web server such as Apache or nginx.
- Have a good understanding of deploying applications within various environments (AWS, GCP, on-prem), from security best practices to continuous integration and containerisation.
- Have good time management and are able to prioritise - there will be multiple projects on the go at any one time.
- Gladly seek out opportunities to speak at meetups or conferences, or otherwise have prior experience as an instructor or teaching assistant.
- Enjoy sharing your knowledge, experience and passion for good coding practices with others.
Please note that we don’t expect all of the above. We know some people are less likely to apply for the role unless they are 100% qualified. Our goal is to promote a diverse, inclusive and empowering culture at Coefficient. If this role sounds exciting to you, please consider applying below. If you’re unsure, please still get in touch — we would love to hear from you.
The successful candidate should be able to travel to London to work on-site for approximately 2-5 days per week once we’re out of lockdown. This means you must be UK-based with eligibility to work in the UK.
📍 Location: We are based in Central London, but we are remote-friendly. You may be required to work on-site at clients’ offices post-COVID.
💰 Salary: £40,000 - £60,000.
🏖 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: Monthly 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, working closely with the founder 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.
💸 CoronaBonus: Additional £50 CoronaBonus per month while we have to work from home to help with things like good internet connection during lockdown. Outside of COVID times, we pay for local co-working spaces for the team.
🎓 Learning and Professional Development: Potential to improve skills through paid courses and a subscription to O'Reilly Online Learning. 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.
📚 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, and lockdown has seen us get inventive with virtual socials, including board games and cocktails!
What to expect from the hiring process:
- Round 1: We look through your application (CV, Cover letter and the code on your portfolio/website/Github/Gitlab) to see if you meet the initial requirements for this role.
- Round 2: You’ll have a 30 minute interview with someone on our lovely Operations Team to get a sense of your personality and your interests outside of Data Science. This is not a technical interview.
- Round 3: We’ll book you in for a 2-hour slot to complete a Code Test, which mirrors tasks you can expect to do at Coefficient.
- Round 4: You’ll have a 1-hour Technical Interview with someone from our amazing Data Team - this includes pair programming and a deeper dive into the required skills for the role.
- Round 5: You’ll have a chat with our CEO, John Sandall, to see if our expectations align.
Applications for the role are considered on a rolling basis and there is no fixed start date. It usually takes us a week to get back to you after each round. Due to a high number of applications, we are unfortunately unable to offer feedback before Round 2. Feedback for subsequent rounds is provided if requested.
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