Data Science and Data Engineering go hand-in-hand and a good data scientist knows solid data engineering skills. In this mixed Junior position, you'll get in your first 18 months a rapid learning & hands-on curve working on the broad Analytics domains: you'll build Data Pipelines, set-up Data Platforms, do CICD, build ML models, do feature engineering, do visualization exercises & lots more. This junior position is a great opportunity to learn end-to-end what it takes to do Analytics end-to-end
Our job offer is there to reflect a mixed data scientist/engineering position: i.e. one where we’ll be asked you to crunch data with the objective to build machine learning models and to embed them in applications end-to-end to production.
As a data scientist/engineer, you aim to work hands-on to deliver data-driven platforms, machine learning models & applications. Every mission we’ll embark will have concrete deliverables and a deadline; this means we can guarantee you a variety of engagements across clients & industries: e.g. one month you might work on a predictive maintenance modelling, another month you might work on a churn model for a marketing client.
You’ll be responsible for (1) platform set-up, (2) data gathering and preparation (3) research on what type of models to use and (3) the ML modelling itself. You will work (standalone or in team) with clients (~50% of the time at the client) and have a responsibility on managing project timeline, status meetings and client coaching & training.
- Build data platforms (data engineering) with Azure and Databricks
- Develop data pipelines & predictive/machine learning models in Python
- Guide customers towards translating their use-case or business idea in platform architectures and machine learning techniques & models
- Act as data science expert on latest machine learning & AI trends
- Be a thought-partner for client data science teams in tackling their specific challenges, limitations & ambitions through machine learning
- Inspire customers with insights, opportunities on new data-driven use-cases
- Act as data engineering expert bringing best-practices of Git, DevOps & CICD to the customer's data platform.
- Embrace project management aimed towards getting the job done. This will include working with client data scientists, data engineers but also business stakeholders
- Be an on- and offline ambassador for the element61 team
Being a data scientist/engineer at element61 means you will work with businesses and executives in Belgium helping them to get a grip on the impact of (big) data, analytics, machine learning & artificial intelligence. As time passes, we’ll encourage you to build a functional expertise within a business or technical domain within your interest such as ad-tech, deep learning, digital marketing, predictive maintenance or other.
- You are already residing in Belgium
- University degree in Computer Science or (Business) Engineering and/or a specialized master in Machine Learning or AI which reflects in
- Knowledge about machine learning approaches and the variety of models which exist & their application area (e.g., SVM, RNN, Deep learning)
- Knowledge about data science basics including sampling and the various evaluation metrics
- Fluent in SQL and Python
- No working experience required; any experience can be a plus
- Knowledge on Spark and/or any Cloud ecosystem (Microsoft Azure, Google Cloud) considered a plus
- Passionate about data, machine learning technology & applications and eager to learn
- Enthusiasm to be part of a growing team & industry
- Fluent in English, Dutch or French is a plus
Are you interested in this opportunity?
Send your curriculum vitae and motivation letter to firstname.lastname@example.org