The team you would join is responsible for the entire lifecycle of data science use cases which can take place in collaboration with one of our external customers or stem from any of the Proximus group affiliates (such as Proximus NV/SA, BICS, Mobile Vikings). Typical use cases can cover domains such as finance, fraud, marketing & sales, logistics, IT, operations and cybersecurity.The vision and ambition of the team you join is
- to create business value by transforming data into actionable insights that drive operational processes or influence strategic decisions.
- to become a Belgian/European reference in AI-driven activities recognized by peers from all sectors.
- to contribute to the Belgian society through various do-good initiatives
Role description
As an NLP Engineer, you will play a key role in developing end-to-end solutions for text analytics and generative AI use cases. By taking up a use case right from the start you will help business define and scope the problem, pick the right machine learning solution and technology as well as ensure implementation, integration and deployment of your solution to production. You will do so while understanding that machine learning is rarely a magic bullet and that clear planning, communication and managing clients’ expectations are vital for project success. You will also collaborate with other team members in knowledge sharing as well as continuously improving our way of work.
Responsibilities
- Help Business scope & shape their AI projects.
- Build a project timeline with the requestor, provide accurate time estimates, and manage expectations.
- Translate business requests into data requirements, extract the required structured and unstructured data from different potential data sources: data lake, data warehouse, Cloud storage, operational systems and prepare large-scale datasets for modelling.
- Identify high-value use cases through data exploration and visualization.
- Develop predictive 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
- Experience with generative AI and prompt engineering on models such as ChatGPT.
- Experience with text analytics tasks such as text classification, sentiment analysis, similarity measurement, text pre-processing, and text summarization
- Experience with training and using transformer models for NLP (e.g., using HuggingFace)
- Experience with multi-lingual NLP projects
- Strong knowledge of state-of-the-art machine learning and statistical methods.
- Experience with the Azure stack
- Hands-on experience with Python and its machine learning ecosystem.
- Proven proficiency in the end-to-end data science project life cycle
Nice to have
- Experience in other ML domains such as forecasting, anomaly detection or computer vision is a big plus
- Experience with the OpenAI API is a big plus
- Experience with multi-modal models is a plus
- Experience with big data ecosystems (Spark, Hadoop) and real-time streaming is a plus
- Knowledge in the field of telecommunications is a plus
Attitudes/Behavior
- Pro-active & driving
- Result-oriented and highly proficient in transforming data into actionable insights that create business value.
- Able to manage data science projects in an autonomous and professional way and drive collaboration with external domain experts, data engineers and other data scientists.
- Team player with strong communication and presentation skills
- Flexible & at ease with Multitasking
- Resistant to stress
- Interested to work on many different short projects.
- Passionate about data science, interested to monitor state-of-the-art and constant learner.
Languages
Fluent in English and Dutch or French.
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