For 10 years, I have been creating value by building concepts and products at the interface between academic research and computational technology first, and then between business and data science. My experiences in biomedical research, HR-tech and consulting allowed me to develop deep scientific skills widened by transversal abilities.
Achievements include expansion of data strategy using proof-of-concepts for national and European-wide companies and development of data science products in production.
- Autonomously explore topics for their application potent e.g. soft skills definition, matchmaking serendipity.
- Improve data assets value awareness with internal web application (ReactJS) and automated customer data quality reports.
- Update / expand existing in-production models for profile/job opening matchmaking (Python/CI/CD).
- Technical debt: code base cleaning and documentation.
- Communication: white paper on AI market in human resources.
- Design and develop a rule-based chatbot for the power market industry (MVP)
- Challenged existing risk assessment models in banking (increased funding by 10% while decreasing risks - boosted trees)
- Design, manage and develop an error detection data pipeline for a major pharmaceutical industry (back and front-end)
- Knowledge transfer to junior data teams (statistical/machine learning models, coding, good practices)
- Pilot, plan and contribute to content production for corporate communication
- Project planning, execution and synchronization: research, collaborative and associative projects in international and interdisciplinary settings - Israël, USA and Sweden (7 completed projects).
- Research: Identification of novel RNAs involved in host / L.monocytogenes interaction (3 published work)
- Teaching and development of wet laboratory procedures.
- Development of bioinformatics workflow for large text files processing and quality control (RNA-Seq / Python).
- Development of next generation sequencing wet lab approaches (RNAs / small RNAs).
- Automation of quality control report generation (R/Sweave ).
- Ensured daily communication in a two-year project between a technological platform and a basic research team.
- Value Proposition Design
- Use case framing
- Process & task planning
- Scheduling & ability to manage simultaneous projects
- Cost management
- Risk analysis
- Data mining/wrangling (python, bash, sed, awk)
- Data pipelines (python, MongoDB, SQL)
- Un/supervised learning (sklearn, xgboost, keras, clustering, LSTM)
- Performance assessment (confusion matrices, residual analyses, business related)
- Data pipelining (ETL)
- Relational and document databases (SQL, MongoDB, ...)
- Implementation (python, html, css, React.js, js)
- Web-application deployment (Docker, virtual hosts, WSGI, ...)
- Continuous integration/deployment (Kubernetes, GitLab)
- Visual communication
- Writing (white paper, data audit, research articles, etc.)
- Critical thinking
- C-level & stakeholder communication