Descrição

  • Flexible remote position : (2 days onsite / 3 days remote).
  • Adress : Av. Infante D. Henrique, Lote 320 - Edifício IDB Lisbon, 1800-220 Lisboa

Job Purpose:

As Data scientist your main objective is to play a critical role in leveraging data to drive continuous improvement within our Command Center. This position will focus on enhancing the reliability and efficiency of our IT production through proactive monitoring and data analysis. The Data Scientist will be responsible for measuring performance, conducting in-depth analysis, and providing actionable insights to support decision-making. Additionally, the role involves creating operational reports and dashboards to facilitate real-time alert management and predictive analysis using Machine Learning and automation techniques.

Main missions :

Key Areas of Responsibility: Within the Command Center, specializing in the monitoring of information systems, dedicated space for collaboration and decision making by exploiting the flow of information. Our mission is to ensure the availability and performance of our information system.

You will be responsible for analyzing logs generated by our alerting tools, creating reports and dashboards in order to implement action plans to reduce the number of incidents and improve our predictive analysis capabilities.

You are able to do both data engineering and data analyses to take part in the scaling of our data platform and support the teams. Within the Data, you will work with the following objectives:

  • Data Management & Engineering
  • Use a Data Lake for collecting, storing, and processing internal and external data oriented on monitoring alerts.
  • Create a robust data pipeline to manage the entire data lifecycle, from collection and cleaning to operational use.
  • Automate data acquisition and processing workflows to improve efficiency.
  • Ensure the scalability, security, and availability of the data platform.
  • Document and maintain best practices for data management systems.
  • Data Analysis & Modeling
  • Analyze logs, alerts, events, and incidents to identify trends and anomalies.
  • Develop and refine predictive models to anticipate incidents and optimize system performance.
  • Use machine learning algorithms to derive actionable insights.
  • Ensure the accuracy and integrity of analytical data, resolving data issues as they arise.
  • Dashboarding & Reporting
  • Create, deploy and automate intuitive dashboards to monitor performance and incidents.
  • Generate detailed reports to track trends and provide decision-making insights.
  • Maintain, update and provide assistance to key stakeholders.
  • Collaborate with stakeholders to ensure data visualization meets their needs.
  • Collaboration & Governance
  • Work closely with IT and business teams to implement data-driven solutions.
  • Contribute to the development of data governance practices to ensure compliance and consistency.
  • Partner with internal teams to explore and integrate new data sources.
  • Continuous Improvement
  • Continuously improve monitoring and supervision processes through data-driven insights.
  • Stay up to date with technological advancements in data solutions and integrate relevant innovations.
  • Anticipate internal client needs and design data structures that are intuitive and forward-thinking.
  • PROFILE :
  • Graduate Degree in Data Science, Computer Science, Statistics, or a related field.
  • +3 years of relevant experience as a data scientist with ideally operational experience in Data platforms among which Master Data Management, BI & Analytics (data warehousing, big data, data science), integration services, Data storage solutions.
  • Proven experience in data analysis, machine learning, and predictive modeling.
  • Proficiency with data science tools.
  • Knowledge of monitoring systems, alerting tools and Service Now ticketing tool.
  • Experience with data visualization and building web apps with Python frameworks.
  • Preference of experience in Insurance or Banking sector and IT Operations
  • Solid understanding of end-to-end data science project lifecycles and Agile methodologies.
  • Project Management experience is a plus.
  • Experience and Technical skills :
  • Programming Languages: Python, SQL, R
  • Machine and Deep Learning Models: Supervised (SVM, Logistic Regression, etc.), Unsupervised (K-Means, LDA, PCA), NLP (BERTopic, Transformers, LLMs)
  • Data Visualization Tools: Power BI (DAX, Power Query, M), Tableau, Kibana.
  • Relational and NoSQL Databases: MySQL, Oracle, MongoDB, SQL Server
  • Soft skills :
  • Analytical thinking, attention to detail and problem-solving min

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