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At GWI we’re always looking for extraordinary people who thrive on making an impact. We think big to make an impact, we’re not afraid to ask why, and we always show respect. Those values are what got us where we are today, and they’re a big part of what we’re looking for in you.
Right now we’re looking for candidates who are interested in working at GWI but haven't quite yet spotted the perfect role within the company. By taking a moment to submit your application and answer a few curated questions, you're not just applying for a job - you're becoming a part of our proactive talent community. This way, as soon as the right opportunity arises that aligns with your profile, you'll be among the first we reach out to.
Who knows, it could be the start of something, well, extraordinary.
About Data Science
Our Data Science department at GWI is committed to maintaining the highest quality in our survey data and to helping our customers arrive at the insights they need to understand their audiences. From automated testing and intelligent product features to custom analytical solutions and data observability, we are supporting the business at every level as data is at the very core of what we do. We are actively engaged throughout the entire data life cycle including data cleaning, data processing, data validation, designing and automating data workflows as well as automatically identifying and recommending insights and unexpected findings to our users.
Our team values learning and keeping abreast of the latest research very highly and as a result we’re applying a wide range of techniques across machine learning, statistical analysis and natural language processing to the services and features we build. We are a diverse team with different backgrounds spread across two locations, Athens and London, and growing rapidly. We are at a very exciting junction where we are experimenting with cloud computing technologies as we want to shift towards full ownership of our own Data Platform.
Roles in Data Science
Our Data Science department is split between the Data Analytics Engineering and Data Science teams consisting of Data Scientists and Machine Learning Engineers reporting to the Team Leads under the VP of Data Science or the Director of Data Analytics Engineering. The teams mainly work with GCP, Python and SQL.
Data Analytics Engineers: You can see this role also referred to as Data Analyst. The role will involve a range of different tasks, with Python and SQL, from transforming and loading datasets to GWI platform, investigating and resolving data discrepancies, working with various stakeholders on the creation and automation of processes and reports, as well as expanding the capabilities of our internal tools. Maintaining ETL/ ELT pipelines for all our datasets and collaborating with Research, Engineering and Product Development teams to design and enhance our bespoke tools.
Machine Learning Engineers: Depending on your background and interest, you will help us shape and realise our data science strategy. Contributing either to building our AI platform - which facilitates the surfacing of relevant and timely consumer insights to our platform users - or developing our data platform - which ingests and augments consumer survey data from around the world. High level of coding proficiency in a technical language such as Python (or R) and a strong-product mindset are valuable skills alongside understanding of information retrieval and recommender systems.
Data Scientists: There are a variety of data modelling tasks performed on our survey data necessary for extracting insights from our growing data assets. From forecasting forthcoming results, to constructing regressions and determining causalities between our different surveys, to understanding multi-scale clustering phenomena. Similarly to ML Engineers high level coding proficiency and technical expertise are valuable assets.
Our benefits
Great benefits make a big difference. Not just to employees, but to the whole vibe of a business. That’s why when you work for us, you’ll enjoy a full spectrum of generous perks, rewards, and office benefits.
- Competitive salary and discretionary bonus
- 25 days annual leave (prorated)
- Hybrid working, flexitime, and a great work-life balance
- Allocated shares according to GWI’s share scheme
- Work from Anywhere policy
- A range of discounts and freebies
- LinkedIn Learning and ongoing Learning and Development opportunities
- Health Shield cash plan for everyday healthcare
- Auto-enroll pension plan with GWI matching up to 4%
- Cycle to work scheme and commuter season ticket loan
- Commit a working day to charity each year
- Early finishes on a Friday
- A well-stocked fridge, plenty of snacks (some healthy, some not so healthy)
- Regular social activities, including free online yoga and team outings
Who we are
GWI was founded with the knowledge that understanding your audience is really important for business. When you know who you’re speaking to and why, you can create content and campaigns that stand out to the people who matter.
Through our global online survey, we gather data on the behaviour and perceptions of consumers across the world. This provides businesses with deep, actionable insights on their audience, revealed from data they trust.
It’s been going well, too. Since launching in 2009, we’ve become one of the UK’s fastest-growing target audience companies. We’re not about to stop growing any time soon. As a business, we’re on a mission to re-engineer data-driven marketing, and we’re on the lookout for talented people to join us.
Diversity & Inclusion
Imagine if our data came from just one kind of person. We’d get a very nuanced view of the world. And we definitely wouldn’t have got off the ground as a business.
Although things certainly aren’t perfect, we live in a society where differences are increasingly celebrated – so we’d expect nothing else from our teams. In fact, the GWI office is as diverse as our global data, it’s really important to us that it stays that way. This is a place to feel at home, express yourself freely, and make your mark.
#LI-DNI
