You will be part of the Advanced Analytics Centre of Expertise, a centralized team of data scientists that is supporting the different business units. You will transform data into actionable insights that drive operational processes or influence strategic decisions. Use cases can be company-wide covering domains such as predictive maintenance, network analytics, operational efficiency, customer relationship management and natural language processing.
- Translate business requests into data requirements, extract the required structured and unstructured data from the data lake, data warehouse and other data sources (e.g. operational systems) and prepare large-scale datasets for modelling.
- Identify high-value use cases through data exploration and visualization.
- Develop predictive and prescriptive models using state-of-the-art machine learning and statistical methods.
- Pilot prototypes in production processes to demonstrate their value.
- Deploy prototypes to production, with support of IT, to obtain reliable, scalable systems.
- Present your results in a clear manner and discuss them with multi-functional project teams.
- Work in close collaboration with business experts (e.g. for requirement gathering, data source identification, data and process understanding, feature engineering, result validation, etc.), with IT (e.g. for ETL, deployment to production, etc.) and with other data scientists in the team (e.g. for knowledge sharing).
Degree & Experience
- PhD or master's degree in a quantitative field (Artificial Intelligence, Computer Science, Engineering, Statistics, Mathematics, etc.)
- 2+ years of relevant work experience in a business environment
- Technical skills
- Strong knowledge of state-of-the-art machine learning and statistical methods. Expertise on deep learning is a plus.
- Hands-on experience with data science technologies such as Python. Experience with big data (e.g. Spark, Hadoop), real-time streaming and cloud technologies is a plus.
- Proven proficiency in the end-to-end data science project life cycle, including:
- Translating business requests into data requirements.
- Identifying high-value use cases through data exploration and visualization.
- Developing machine learning solutions (incl. feature engineering, model fitting, etc.).
- Deploying scalable machine learning applications to production.
- Passionate about data science and a constant learner
- Result-oriented and highly proficient in transforming data into actionable insights that create business value
- Team player with strong communication and presentation skills
- Able to manage data science projects in an autonomous way and to drive collaboration with domain experts, data engineers and other data scientists
- Knowledge in the field of telecommunications is a plus
- Fluent in English and preferably also Dutch and/or French.