Data Scientist

Key Skills

Aartificial intelligence, AWS, Azure, Data science techniques, Data Visualization, Deep Learning, Effective communication skills, Google Cloud Platform (GCP), Machine learning techniques, Natural Language Processing (NLP), NoSQL, PowerBI, Python Programming, SQL, Tableau

Job Description

At Sanofi, we’re committed to providing the next-gen healthcare that patients and customers need. It’s about harnessing data insights and leveraging AI responsibly to search deeper and solve sooner than ever before. Join our Global Digital Team as Senior Data Scientist and you can help make it happen. Your job? You are a dynamic data scientist interested in challenging the status quo to ensure development and impact of Sanofi's AI solutions for the patients of tomorrow. You are an influencer and leader who has deployed DSC/AI/ML solutions applying state-of-the art algorithms with technically robust lifecycle management. You have a keen eye for improvement opportunities and a demonstrated ability to deliver AI/ML solutions while working across different technologies and in a cross-functional environment.

At Sanofi Consumer Healthcare, we build trusted and loved brands that connect with hundreds of millions of consumers worldwide. Our mission is to enable better self-care for individuals and communities, while also contributing to a healthier planet. We strive to act as a force for good by integrating sustainability along our business and employees’ mission and operate responsibly from both a social and environmental point of view. To achieve this, we need people who can shape the future of our business and help us on our journey to becoming the best fast-moving consumer healthcare company in and for the world.

Main Responsibilities

• Hands-on AI/ML modeling experience of complex datasets combined with strong understanding of theoretical foundations of AI/ML.

• Establish and drive data hygiene best practice to ensure coherence and integrity of data feeding into production ML/AI solutions.

• Collaborate with colleagues across science and engineering disciplines for fast turnaround proof-of-concept prototyping at scale. Work closely with stakeholders, developers, engineers, and MLOps to deliver AI/ML solutions.

• Wide Application of Expertise: Apply data science expertise in machine learning, statistics, text-mining/NLP, forecasting and optimization to multiple analytics projects.

• End-to-End Process Understanding: Strong understanding of the end2end process, from POC to MLOPS. Use data analysis, visualization, storytelling, and data technologies to scope, define and deliver AI-based data products.

• Model Development: Conceptualize, Build models, algorithms, simulations, and experiments by writing highly optimized code and using state-of-the art machine learning technologies.

• Full Spectrum Activities: Involved in the entire spectrum of activities from ML experiments to delivering production-ready models.

About you

Key Technical Requirements & Qualifications:

• Experience Requirement: Seeking candidates with over 5 years of experience in similar roles, indicating a senior position and advanced level of English. Nice to have: experience in life sciences and healthcare and experience in a complex global organization

• Educational Background: PhD in mathematics, computer science, engineering, physics, statistics, economics, or a related quantitative discipline with strong coding skills, OR Master’s Degree in relevant domain with solid analytical experience.

• Programming Skills: Expertise with core data science languages (such as Python, R, Scala), and familiarity with different database systems (e.g. SQL, NoSQL).

• Strong programming experience and repositories experience – interest for continuous improvement.

• Documentation: Experience documenting modeling for technical and business leaders.

• CI/CD Proficiency in implementing CI/CD pipelines specifically designed for data science projects. MLOPs: Demonstrated experience in implementing MLOps practices to streamline the deployment and lifecycle management of machine learning models.

• Data Visualization Tools: Knowledge of tools like Tableau, Power BI, Plotly, or similar. API Experience: Experience with various enterprise-level APIs for integration purposes.

Given these requirements, the ideal candidate would be a senior data scientist with strong technical skills, extensive experience in AI/ML, excellent communication and collaboration abilities, and a track record of delivering impactful solutions in a cross-functional environment.