About Geoblink

We’re a fast-growing startup that has already raised close to €10 million in investment from leading venture capital firms and has 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 Management and the way businesses think about and act upon location 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 provides lots of awesome statistics and 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 Junior Data Scientist passionate about finding, processing, and modeling data to solve real-world problems. You would be one of the main points of reference for clients 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 as Data Scientist. The candidate should have a solid foundation in the relevant technical concepts and principles.
• You have the ability to approach complex problems with analytical capabilities and critical thinking skills, enjoy facing challenging problems, and are able to apply logical reasoning to find solutions.
• Proficiency in Python programming, including the ability to write functions and classes. You must be comfortable using Python as your primary programming language and be willing to learn and apply additional patterns and best practices.
• Some experience in analyzing data using Python and common libraries such as Pandas and Scikit-learn.
• 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.
• A good understanding of statistics, including probability theory, and familiarity with common machine learning techniques such as decision trees and clustering algorithms.
• Some experience with SQL queries and an understanding of different types of joins. Junior data scientists should be able to retrieve and manipulate data from relational databases effectively.
• Familiarity with Linux systems and comfort working through the command line. This means being able to navigate and perform tasks using the command line interface.
• Excellent written and verbal communication skills, particularly the ability to explain complex analyses to non-technical audiences (stakeholders and clients) in Spanish and English.
• An understanding of how to find a balance between real-life constraints (e.g., deadlines, available data) and desired outcomes (e.g., accuracy, overdelivery).
• Passionate about what you do. You care deeply about the things you build.

You will get extra kudos if you have:

• Client-facing experience.
• Experience working on projects involving data analysis, such as (for example) Kaggle challenges or personal projects, to demonstrate their understanding of the main steps in data analysis.
• Fluency or understanding of German, French or Dutch.
• Knowledge or experience working in a cloud based environment (AWS, GCP…)
• Knowledge or experience working with distributed databases like Google BigQuery
• Knowledge or experience working with spatial data or GIS systems and/or mobility data.
• You are familiar with writing Python packages and tested code (e.g. PEP8, Pytest…)

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:

• Enrich our database of points of interest and points of sales: you may master techniques of web scraping, manage exclusive providers of spatial data.
• Analyse the most extensive and complete spatial database to understand the retail and/or real estate ecosystem, consumer's behaviour patterns, etc.
• Load & Extract data from our datalakes and databases (relational and non-relational) to support clients or build reports.
• Design, develop, monitor and maintain a wide range of explanatory and predictive models and integrate them into the production environment so users can make predictions in real time.
• Work closely with the rest of the team including Business profiles, the Customer Success team, and other Data Scientists and Software Engineers to understand everyone’s needs and develop optimal solutions.
• 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:

• Competitive salary and the option to join the phantom shares company plan.
• 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.
• Flexible remuneration: restaurant tickets, transport tickets, private healthcare and childcare.
• Plenty of training initiatives to help your career progression
• Annual personal budget for you to spend on developing yourself (online courses, conferences, training, etc)
• Start-up culture with fun initiatives and company events for all to enjoy

Diversity Statement

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.