Join us on our mission to connect the next generation with the opportunities, insights and advice to succeed as the workforce of tomorrow!Apply Now!
Join Bright Network as our Data Scientist!
Click here to apply or scroll down to read more!
About Bright Network
Bright Network is the UK’s leading website for graduate career advice and job search, with very high levels of engagement and net promoter score. We are very focused on user-centered design with the undergraduate member experience at the heart of everything we do. We’re also focused on using data to improve the member experience by making everything we do relevant, targeted and personalised.
We have an engineering team of 11, based in Edinburgh and across the UK: 9 full stack engineers, 1 frontend engineer and a product manager. We are looking for a data scientist to join the team to work on a range of data projects, but with particular focus on our recommendation engine.
We have just built the first version of our our recommendation engine to suggest suitable jobs to graduates based on their profiles and behaviour data, and also use it to allow graduate employers to target groups of graduates who will be interested in their opportunities. By solving this matching problem we’re trying to improve the access to opportunities which each undergraduate member gets, and also allow firms to extend their reach beyond their established graduate intake.
This is a great opportunity for the data scientist to have a major impact on the future of data science within Bright Network, and lead us on the journey to solving the matching problem between graduates and graduate employers.
We’ve worked really hard to build the engineering team and culture that we want to work in, and we all believe we’ve built something very special. We are focused on trying to do world-class engineering, using the right tools and processes to build high-quality, scalable and user-centered products and platforms. Given the data we’ve built up on our undergraduate members, we are now putting data science and data at the heart of everything we do.
Engneering culture & best practices
- Continuous deployment to production
- Metrics and data driven decision making
- Highly flexible working culture – a focus on doing great work and achieving great results with less on focus on working hours or how you do this
- Incredibly autonomous engineering team – the company feed into the long term roadmap priorities but engineering and product then have autonomy to deliver as they see fit
- We allocate at least 10% of every sprint to technical debt, architecture and refactoring
The technology stack
- We use collaborative filtering algorithms, helped with natural language processing (NLP).
- It relies mainly on python3, pandas, scikit learn and nltk
- Our data is mainly stored in an elasticsearch cluster
The ideal candidate
- Significant python experience
- Solid machine learning / data science experience, ideally in a "real world" challenge
- Good understanding of Pandas, Scikit learn, nltk / tensorflow
We can offer you
- A high-growth and rapidly scaling business (we recently secured £3.5 million in funding)
- A flat & transparent structure with a values-driven & collaborative culture (which you can hear more about here!)
- A culture of flexibility & trust where you have access to an unlimited holiday allowance & flexible / hybrid-working policies
- £50 per month flexible wellbeing budget to be spent on the wellbeing benefits of your choice through our benefits platform
- Annual company-wide bonus scheme
- Enhanced pension contribution through Aviva
- Private healthcare plan
- Enhanced parental leave policy
- Sales introduction & employee referral schemes
- A culture of constant growth & improvement, with monthly lunch & learns & ad-hoc training budget for team or individual training
- Regular team socials including our annual full team off-site, Christmas Party and other celebrations!
- Salary : Highly competitive
- Location : Edinburgh – preference for 1 day a week in the George Street office when restrictions allow
- Start Date : ASAP