Software Engineer & Data Scientist

Joined the AI and data science team of a recruitment platform to design and develop an AI-based hiring system for HR clients.

• Designed and developed an AI-powered recruitment platform, automating candidate application processing.
• Implemented NLP-based interview question generation from candidate CVs and job descriptions.
• Built automated candidate evaluation and scoring models, providing real-time analytics for HR decision-making.
• Developed interactive dashboards to visualize candidate progression, performance metrics, and recruitment KPIs.
• Engineered end-to-end pipelines covering job posting, interview processing, analytics, and report generation.
• Technical environment: Python, Flask, MongoDB, Hugging Face NLP models, LLM pipelines.

Joined the data science team of a BI and digital strategy consulting firm to develop forecasting models applied to logistics.

• Developed forecasting models to predict container throughput using Python and machine learning techniques.
• Built Flask backend APIs to integrate ML predictions into interactive dashboards.
• Technical environment: Python, SQL, Flask, Machine Learning.

Participated in a business intelligence mission within a data analytics team to modernize financial forecasting and workflow automation.

• Developed predictive models for financial forecasting using regression techniques.
• Automated ETL workflows to streamline data integration via SSIS and Power Automate.
• Designed interactive Power BI dashboards with advanced DAX calculations to monitor KPIs.
• Enabled data-driven decision-making for financial and business operations.
• Technical environment: SQL, Power BI, DAX, SSIS, Python.

Joined the big data team of a telecom operator to process and analyze telecommunication data at scale.

• Configured Hadoop and HBase ecosystem for large-scale telecom data processing.
• Applied Apache Spark for distributed analysis of call data records (CDRs).
• Extracted actionable insights to support telecom service optimization.
• Technical environment: Hadoop, HBase, Apache Spark, Python, SQL.