Aixcs Data Scientist

The team you will join (AI business development) is responsible for the development & delivery of high-quality innovative AI solutions (E2E) the external customers of the Proximus Group. Our vision is to be a recognised, trusted, and valued partner for AI transformation and secured AI solution delivery & deployment on the Benelux market. As we are centralizing the expertise in AI and CS, we want to distinguish ourselves by creating value with projects at the intersection of those two advanced disciplines by creating solution to tackle Fraud (smishing, vishing, spoofing,), detect malwares and cyber-attacks, proactively protect enterprises networks, etc. If you are willing to contribute to our growth by inspiring and helping new customers, this job is made for you.

Role description

As an AIxCS Data Scientist, you will play a key role in the complete lifecycle of AI solution creation and delivery for cybersecurity (CS) or fraud related use cases. 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.

In the team, you will be the single point of contact with respect to this AIxCS field and will be recognised as our internal expert in the field. You will collaborate with other data scientists to exchange best practices and with Analytics Translator to help them get new projects in that domain.

**Responsibilities**:

- Develop and centralize knowledge and expertise in AI for CS
- Follow up on news in AI regulations & privacy laws to be our go-to person for GDPR & AI act related questions.
- Demystify AI & represent our AIxCS expertise to our client (presentation, events, training)
- Drive AIxCS innovation in Proximus Ada & work on internal projects & POC’s
- Help clients identify cybersecurity needs that could be answered by leveraging AI models.
- Answer RFP’s to get new projects
- Go through research papers to identify best way to tackle problems.
- Design AI solution architecture on prem or in the cloud
- Fully manage AI project from inception to production on your own:

- Translate business requests into data requirements.
- Scope the project and support business case creation,
- Build a project roadmap with the requestor, provide accurate time estimates, and manage expectations.
- Collect, extract, analyse and prepare data,
- Develop predictive models using state-of-the-art machine learning and statistical methods,
- Pilot prototypes in production processes to demonstrate their value,
- Deploy the ML flow to production in a fully secured way,
- implement feedback loop and ensure model proper monitoring & retraining,
- Present your results along the way in a clear & accurate manner,
- You will accomplish all this by working 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 of 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.)
- **3+ years of relevant work experience in machine learning**:

- Previous consultancy experience would be ideal but is not required.

Technical skills
- **Strong knowledge and experience with fraud detection techniques, algorithms, and concepts: anomaly detection, profiling/segmentation, behavioural analysis, forecasting or NLP.**:

- **Strong hands-on experience with Python and its machine learning ecosystem.**:

- **Good knowledge of AI regulations & privacy (GDPR, AI act,)**:

- Hands-on Experience with Cloud technology (Azure)
- Strong knowledge of state-of-the-art machine learning and statistical methods.
- Deep learning framework (e.g. Tensorflow, PyTorch) & big data (e.g. PySpark, Hadoop)
- Hands-on experience with Linux and Hadoop commands
- Any experience with the following elements is a big plus:

- Applied Generative AI
- MLOps practices, e.g. orchestration with Airflow, Gitlab CI/CD, etc.
- Containerized deployment of ML products - e.g. docker, podman, Kubernetes
- Explainable AI

Soft skills
- **Experience in project management, stakeholder management and expectations management**:

- **Strong communication and presentation skills**:

- Familiarity with agile framework

Attitudes/Behaviour
- Passionate about data science and cybersecurity
- **Motivated to learn, grow, and specialise in the AIxCS domain.**:

- **Proactive, can-do and solution oriented**:

- **Capable of driving a project even in a blurry context**:

- Result-oriented and highly efficient 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 engine