Summary
I'm highly cross-functional and committed to creating value in complex, uncertain environments through human-centered, frugal, and pragmatic approaches. I believe data science products should offer the best choice architecture for users and decision-makers, focusing on making technology serve people, not the other way around.
Work Experience
- Manage the delivery of concurrent data-driven projects (different industries and teams) overviewing multi-disciplinary teams (data science, tech and consulting)
- Lead a craft-based vision to technical project delivery (scale-proof code base management, lead internal asset management with an Ops highlight)
- Industrialize data science projects in hybrid environments with Tensorflow models from proof-of-concept with data acquisition to run (ongoing scale)
- Coach and supervise data science consultants (up to 7 people at the same time on delivery projects)
- Quickly modulate outreach level in stakeholder meetings (presales, exec committees) to maximize impact
- Shape and deliver technical product vision aligned with business requirements, technical capabilities, available human resources, costs and product lifecycle
- Conduct regular semi-directive hiring interviews to assess both technical and transversal skills
- Scientific leadership on deep learning based projects (computer vision and generative)
- Domain knowledge : pharma industry (clinical science, R&D) and public services
Benefiting from an interdisciplinary background, provides expertise on
both methodological and technical aspects of data fueled innovation projects.
- Increase online sales in response to Covid19-accelerated digitalization for a worldwide retail sports industry (recommendation engine).
- Identify levers and prioritize use cases for a healthcare firm with organizational barriers.
- Enhance brand visibility:
- Scientific leadership in an open collaboration project in the media sector.
- Improve inbound marketing strategy (content creation, e.g. Weblog Wemanity).
Collaborate with data, product and customer success teams to bring pragmatic
solutions to build an artificial intelligence based career coach.
- Showcase technology assets to business teams and improve data capital (web applications).
- Build market niche expertise: white paper on AI market in human resources (inbound marketing).
- Lead R&D initiatives to improve user engagement (serendipity in recommendation engines results).
- Build up the SaaS core functionalities with client feedbacks in an agile continuous deployment environment (update in-production machine learning models).
Manage and deliver data science projects from scoping to planning, execution
and defense in front of stakeholders - average project duration 2/3 months.
- Enhance operational efficiency with a minimal viable product client support chatbot for the power market industry.
- Raise awareness of organisational silos during the development of an error detection pipeline for a major french pharmaceutical industry.
- Increase funding rate (10%) and lower the risks by replacing a rule-based model with a machine learning model in a credit default application.
- Coaching of junior data teams (statistical/machine learning models, coding, good practices).
In vitro and in silico academic research on RNA biology and infectious diseases in international projects.
Skills
Strategy
- Value creation strategies (Value Propostion Design, System thinking, OKR)
- C-level executives and stakeholders communication
Operational
- Leadership & Team work
- Agile methods
- Cost management
- Business intelligence
Scientific & Technical
- Data Science (mining, modelling)
- Data & software engineering (Web / SaaS)
- Biology & Bio-informatics
Analytic
- Conceptualization
- Risk analysis
- Critical thinking
- Synthesis (research articles / audits)
Publications
Volunteer Work
Communication development and design thinking of a conference (in the
organizing association).
Awards
Predicting duration spent by a car on the test bench