We’re a fast growing startup that has already raised close to $8 million in investment from leading venture capital firms, and have been named by Bloomberg as one of the 50 most promising startups in the world to look out for. Our goal is to revolutionise the world of Location Intelligence and the way businesses think about, and act upon location intelligence data.
At Geoblink we use the latest technologies to find solutions to real world problems businesses face when trying to expand or increase efficiency. We leverage GIS technologies and Big Data to create a beautiful map-based user interface that not only provides lots of awesome statistics but also a great user experience.
We are proud of the environment of collaboration and diversity we have built and continue to foster, with plenty of opportunities to have a real impact on the business.
About Geoblink Tech
Our systems are built using an SOA approach that allows us to perform multiple deployments per day. We <3 monitoring, pull requests, iteration, continuous deployment and automated testing. The trunk of our stack is Python, Scala, Spark, Node.js, Vue.js, PostgreSQL and Google BigQuery but our architecture is language-agnostic. We move fast but put a lot of thought into the design of our architecture so that it’s simple and scalable. We write clean, modular code to produce great software that solves the needs of our clients.
Our Tech & Data culture is based on the high standards we try to achieve in everything we build and the personal development of our team. We foster an inclusive atmosphere of non-ego and respect where ideas are shared and feedback is used to promote quality and innovation. Some initiatives we have in place are hackathons, bi-weekly Tech & Data talks, personal development budget for books, training and conferences and time for side projects when possible.
You can visit our Tech blog to learn more about the projects and technologies at Geoblink.
About Data Labs team
Data is at the heart of all the technical challenges at Geoblink. As a Data Scientist at Geoblink you will be part of a team called Data Labs, responsible for answering business questions vital to our clients, based on data. Geoblink relies on a large amount of spatial datasets to model urban behaviour, which can be used to make decisions such as where are my competitors? Which is the best location for a new site? Which features are driving my sales? Is my point of sale under/over performing with respect to its potential?
Our dataset streams come from both internal data (coming directly from our customers for their own use) and external data (retrieved, cleaned and prepared internally at Geoblink from over 60 sources), which are used to deliver analyses and insights allowing our customers to understand their current and past business situation (descriptive analytics), providing them with models and tools to be able to predict the impact and effects of potential business actions and decisions (predictive analytics) and, at a higher level, recommend them which of those actions and decisions should be taken to maximize their final revenue (prescriptive analytics). To do so we rely heavily on Python, and more precisely, on three different types of technology: data management and analysis tools (e.g. Pandas, Matplotlib, Seaborn, Plotnine, Jupyter…), machine learning frameworks (e.g. scikit-learn, LIME…) and software development oriented libraries (e.g. Flask, Pytest..)
Who we’re looking to recruit
We are looking for a Data Scientist passionate about finding, processing and modelling data to solve real world problems. You would be one of the main points of reference to, given a business problem, figure out how to solve it with the existing datasets, or how to find out those which could be useful to complement the existing ones.
Here are some other things we’re looking for:
- BS or MS degree in Physics, Math, Computer Science or related degree or experience.
- You enjoy being challenged with unsolved problems that you need to figure some creative solution out.
- Hands-on experience working on the whole life cycle of predictive models development (data preparation, feature selection, feature engineering, outlier detection, model selection, optimization, evaluation and final deployment).
- Knowledge and experience in advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.).
- You have an excellent understanding of machine learning techniques and algorithms, such as k-NN, SVM, Decision Trees, Random Forests, XGBoost, etc., although you are aware that the best solution sometimes is the simplest, and you know when to use one or another solution.
- Good coding skills in Python with high quality standards and deep knowledge of the main Python libraries and tools focused on data analysis and machine learning (e.g. Numpy, Pandas, Jupyter, scikit-learn, matplotlib, etc.).
- You craft elegant, structured and tested code (e.g. PEP8, Pytest…) and are used to working with code repositories as part of a team (e.g. Git, peer code review…).
- You have experience working with relational databases.
- Excellent written and verbal communication skills, you are able to explain, in English, complex analysis to non-technical business-driven people (stakeholders and clients).
- Passionate about what you do. You care deeply about the things you build.
You will get extra kudos if you have:
- Experience working in a cloud based environment (AWS, GCP…)
- Experience working with distributed databases like Google BigQuery.
- Experience working with spatial data or GIS systems and/or mobility data.
- Experience in spatial Econometrics.
What you can expect from the job
At Geoblink, we embrace evolution and changes, so you need to be prepared to evolve and change with the rest of the company. With that in mind, these are the sort of things you can expect to be doing:
- Design, develop, monitor and maintain a wide range of explanatory and predictive models and integrate them into the final app to allow our customers to better understand their current and future business.
- Analyse the most extensive and complete spatial database to understand the retail and/or real estate ecosystem, consumer's behaviour patterns, etc.
- Enrich our database of points of interest and points of sales: master techniques of web scraping, manage exclusive providers of spatial data.
- Coach and mentor other team members to create a culture that fosters collaboration and personal growth.
- Work closely with the rest of the team including Product Owners, Data Scientists and Software Engineers to understand everyone needs and develop optimal solutions.
- Actively collaborate in the different initiatives the company works on regarding brand awareness (e.g. blog, meetups, talks, etc.)
- Learn as much as you can.
Why work for Geoblink?
We operate a “zero-policy” which means there are no restrictions on vacation days, office hours, working from home days, etc. We believe everyone here is a “mini-CEO”, and should have the opportunity to make their own decisions about their work schedule.
Everyone at Geoblink is passionate about their job, whether it be growing business ROI or building complex data systems. People join us not just for the flexibility that we offer but because we have worked hard to foster a collaborative environment filled with plenty of opportunities to have a real impact in the business and collaborate with smart peers. We also offer the following:
- Plenty of training initiatives to help your career progression
- Annual personal budget for you to spend on developing yourself (online courses, conferences, training, etc)
- Flexible remuneration: restaurant tickets, transport tickets, private healthcare and childcare
- Start-up culture with fun initiatives and company events for all to enjoy
- Company shares after 1 year of employment
- No restrictions on vacation days, office hours, working from home days, etc. You manage your own work schedule responsibly.
- Hybrid WFH Work Model: you choose where to work, whether at home or in the office.
Geoblink is passionate about creating an inclusive culture that encourages, supports, and celebrates the diverse voices of our employees.
Everyone is welcome and we don’t discriminate on the basis of any protected characteristic including race, religion or beliefs, gender or gender, age, sexual orientation, marital status, or disability.
We want to facilitate everyone in bringing their best to our interviews, so if there are any adjustments we can make for our process to be more inclusive, please let our team know.