Senior Data Scientist (M/F)

In the TOP10 of Engineering Consulting Companies in France, the SCALIAN Group operates in service activities for industrial project management, supply chain, architecture and development of embedded digital systems, information systems applications, and Artificial Intelligence in sectors as varied as aeronautics, space, automotive, railway, services, luxury, or retail, etc. Created in 1989, SCALIAN today has more than 5500 employees distributed across 11 countries and 15 locations in France for a turnover of 550 million euros. SCALIAN works for major CAC40 Groups on projects in AT or fixed-price. Labeled Great Place to Work, SCALIAN experiences 20% growth every year. Why SCALIAN? Because Scalian supports you in the development of your career: complete 1-year onboarding program with your manager and your HR, personalized training programs, technical communities, internal events Because Scalian promotes Quality of Life at Work: Great Place to Work® and Best Workplaces for Women certifications, referral bonus, vacation bonus, teleworking agreement Because Scalian develops a concrete and ambitious CSR policy: sustainable mobility, environmental actions, disability actions (approved agreement, inclusive recruitment process, training for managers and recruiters, disability mission with dedicated time: missionhandicap@scalian.com )

Job offer: Senior Data Scientist (M/F) Location: Paris Teleworking: 2 days of TT, 3 days on site Contract type: CDI (Freelance not accepted) Remuneration: Up to 65 K€ depending on profile Start date: As soon as possible Required experience: Senior profile with strong expertise in Data Science, Machine Learning and MLOps industrialization Duration: Long mission About the position: Industry sector: Banking Main objectives: Design, develop and industrialize Machine Learning and AI models as part of a strategic program, aiming to improve the digital experience of customers on a mobile application. Role within the team: Integrate the Data Chapter and collaborate with several squads (6 squads) in an agile, API and event-driven oriented environment, with high requirements in terms of performance, security and quality. We are looking for a Senior Data Scientist to work on high business value use cases, from the scoping phase to production and the RUN of the models. You will be a key player in algorithmic design, while ensuring a relay role between business, technical and product teams.

Your missions: Data Science & Modeling:

Work with squads on business use cases: scoping, choice of algorithms, identification of relevant data and methodological approach.

Exploration & Prototyping:

Analyze data, experiment with different models, evaluate their performance and validate hypotheses.

Development & Industrialization:

Optimize models, build data pipelines, deploy to production and implement monitoring systems.

Innovation & Algorithms:

Develop prediction, recommendation or optimization models (research, targeting, trend anticipation).

MLOps & RUN:

Industrialize the deployment of ML/AI solutions on different environments and ensure their maintenance in operational conditions.

Communication & Popularization:

Present and explain results to a non-technical audience (business, PO, stakeholders).

Technical environment (Stack): Languages: Python, Scala, Bash

Data & Processing: Spark, distributed computing

Cloud & Platforms: AWS (SageMaker), Kubernetes, Cloudera

Databases: SQL / NoSQL

Machine Learning: Scikit-learn, Pandas, NumPy, PySpark, other ML frameworks

Industrialization: CI/CD, Git, unit tests, MLOps pipelines

Profile sought: Confirmed mastery of data pipelines under Azure and Python development.

Ability to work in an Agile environment with a strong Software Craftsmanship culture.

Fluent English is imperative (international context).

Communication skills to interact effectively with business and cross-functional roles. Additional assets: Knowledge in Data Science is a plus to collaborate on data contextualization topics.

Profile sought: Strong expertise in Data Science and Machine Learning (design, training, optimization of models) Significant experience in model industrialization (MLOps) and production deployment Mastery of distributed environments (Spark) and modern data platforms Ability to evolve in a multi-squad Agile environment Solid project management skills (scoping, monitoring, animation, reporting) Excellent analysis and synthesis skills Soft skills: Strong sensitivity to business issues, especially banking Excellent communication to popularize complex subjects Rigor, critical thinking and organizational skills Interpersonal skills to interact with cross-functional teams Additional assets: Knowledge of the banking sector (GDPR, financial products, compliance, risks) Experience with API and event-driven architectures Appetite for digital user experience issues