Lead Data Scientist

ABOUT US

Namirial is a multinational company specializing in Qualified Trust Services and technology solutions that help businesses, professionals, public administrations and individuals manage digital transactions.

Namirial has more than 1000 employees in its 30 offices in Europe, Latin America and Asia. It is active in more than 85 countries, with a network of clients and more than 200 business partners worldwide. We are on the EU Trusted List as a Qualified Trust Service Provider (QTSP) according to eIDAS and eIDAS 2 requirements. The most authoritative independent analysts rank us among the world’s leading providers of Digital Transaction Management.

Our international experience and knowledge of the different markets we work in, which we have developed together with our clients and partners, make us one of the leading global technology players.

Within Namirial, the Namirial KYC / Onboarding solutions use internally developed services to perform automated key information extraction, fraud detection and other document processing tasks on various kinds of documents, from official ID documents to various kinds of supporting documents. It uses a wide variety of techniques to counter constantly evolving fraud methods, including AI-based image processing and natural language processing.

ROLE DESCRIPTION:

The Lead Data Scientist is a senior data scientist who leads the team that researches and maintains the various AI services used by the other teams to perform key information extraction, fraud analysis on documents, and other document processing tasks.

Reporting to the Team Lead Manager and working with a team of diverse backgrounds (research or software-delivery oriented) and various levels of seniority, the Lead Data Scientist leads initiatives, from the research project to their implementation and maintenance in a production context. She or he ensures adherence to proper methodologies, adequate tooling, and that the team keeps being properly trained and updated on advances of both science and business domain issues.

In collaboration with the Team Lead Manager, Product Owner, and other team leads, the Lead Data Scientist ensures that the research efforts match the business objectives and participate in the definition of the roadmap.

RESPONSIBILITIES:

The lead data scientist’s main tasks are as follows:

• Follow the state of the art, research and evaluate current approaches, and ensure the knowledge is shared across the team

• Prototype and develop machine learning / deep learning-based algorithms to address business objectives

• Lead research projects from the original idea to the industrialization in production

• Align the team on proper research methodologies, on documentation and information sharing practices, on software delivery good practices

• Ensure the team can achieve data-driven decisions and evaluations of different approaches

• Define and specify tooling, contribute to defining budgets

• Ensure that the models’ performance and quality in production is satisfactory, contribute to the definition of metrics and KPI

• Ensure that the team keeps being coached and trained, especially new hires and more junior members

• Lead collaboration with third parties (subcontractors or other researchers)

• Ensure current legislation and data processing regulations compliance (GDPR, CNIL, IA Act)

TECHNICAL SKILLS:

• Deep Learning / Machine Learning

• Python, TensorFlow, PyTorch

• Git / dvc

• Docker / Kubernetes

• Finding and analyzing state of the art research papers

KNOW-HOW:

• Leadership

• Research project management

• Teamwork

• Cross-functional collaboration with teams/partners

• Curiosity and depth

• Adaptability/Resilience

• Commitment, reliability

• Problem solving, creativity

ORGANIZATIONAL:

• Organizational and time management skills

• Meeting deadlines and transparency about progress

• Compliance with defined priorities

• Respect for processes and tools

OTHER:

• Fluent French

• Professional proficiency in English

PROFILE:

• Training/ studies: Master, Engineering Diploma, or PhD in Data Science, Computer Science, Mathematics or similar

• Level of expertise: Senior