Cyber Security Data Scientist
il y a 2 semaines
The team you would join is responsible for the entire lifecycle of data science use cases which can stem from any of the Proximus group affiliates, such as Proximus NV/SA, BICS, TeleSign. 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 our networks, etc. anything that would help securing the Proximus Group even better and make the Belgian society benefit from it.
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** and **CS** driven activities recognized by peers from all sectors;
- to contribute to the Belgian society through various do-good initiatives.
Your Role
As a Data Scientist, you will play a key role in developing end-to-end solutions for **cybersecurity** 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 in a fully secure way. You will do so while ensuring that our internal governance processes and best practices are respected. You will also collaborate with other team members in knowledge sharing as well as continuously improving our way of working.
**You will**:
- 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;
- Go through research papers to identify best way to tackle the problem;
- 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 and **cybersecurity** analysts in the team (e.g. for knowledge sharing).
**Your Profile**
- PhD or Master's degree in a quantitative field (Artificial Intelligence, Cybersecurity, Computer Science, Engineering, Statistics, Mathematics, etc.);
- Strong knowledge of state-of-the-art machine learning and statistical methods;
- Strong knowledge in fraud detection techniques (behavioural analysis, anomaly detection, network threats identification,);
- Extensive understanding of security concepts, security domains and security tools, their implementation/usage in large IT and Telco environments (on-premises or in the cloud);
- Hands-on experience with Python and its machine learning ecosystem;
- 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.);
- Knowledge of Windows, Linux, internet technology and network protocols;
- Any experience with following elements is a **big **plus:
- Cloud technology (AWS, Azure);
- Telecommunication networks & products (5G, SS7, IoT,);
- Any experience with following elements is a plus:
- MLOps practices, e.g. orchestration with Airflow, Gitlab CI/CD, etc;
- Containerized deployment of ML products - e.g. docker, podman, Kubernetes;
- Splunk;
- Deep learning (e.g. Tensorflow, PyTorch), big data (e.g. Spark, Hadoop) and real-time streaming.
- Passionate about data science & **cybersecurity**;
- Curious, constant learner and happy to do research;
- Integrity & trust while managing confidential information;
- 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 drive collaboration with domain experts, **cybersecurity analysts**, data engineers and other data scientists;
- Fluent in English and preferably also Dutch and/or French.
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