Job Description

- Apply data science expertise in machine learning, deep learning, statistics, text-mining/NLP, forecasting, and optimization to multiple analytics projects.

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

- Work on a full spectrum of activities, from conducting ML experiments to deliver production-ready models.

- Use data analysis, visualization, storytelling, and data technologies to scope, define and deliver AI-based data products.

- Work closely with product owners, developers, engineers, and MLOps to deliver AI/ML solutions.

- Adhere to and promote best practices and standards for data science process (including documentation) and code developments.

- Remains up to date with industry practices and emerging technologies such as generative AI and tests creative ways of offering AI solutions to enhance existing solutions.

Key Functional Requirements and Qualifications:

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

- Expertise within most of the following areas: supervised learning, unsupervised learning, deep learning, reinforcement learning, federated learning, time series forecasting, Bayesian statistics, optimization

- Experience creating and deploying code libraries using functions, and classes in Python in AI product-focused development in an agile environment.

- Comfortable working in the cloud and high-performance computing environments (e.g., AWS, GCP, Databricks, Apache Spark)

- Experience in production-ready software development

- Experience in communicating with businesses, expressing important DS concepts in a non-technical way, interpreting feedback from business.

- Excellent written and verbal communication, business analysis, data visualization, and data storytelling skills

- Nice to have experience in life sciences and healthcare and experience in a complex global organization.

- A demonstrated ability to work and collaborate in a team environment.

- Ability to work in a fast-paced, constantly evolving environment and to manage multiple priorities.

Key Technical Requirements and Qualifications:

- Ph.D. in computer science, mathematics, physics, statistics, or a related quantitative discipline with strong coding skills with 2+ years of analytical experience, OR Master\'s Degree in a relevant domain with 4+ years of analytical experience

- Expertise with core data science languages (predominantly with Python, and nice to have R & Scala), experience working with Snowflake and other different database systems (such as SQL, NoSQL)

- Should have experience of AI/ML development (CI/CD, Orchestration)

- Experience working in a cloud-based environment such as AWS or GCP or Azure and using cloud technologies for building AI-solutions.

- Knowledge of Tableau, Power BI, Plotly, git/version control systems, or similar

- Experience with various enterprise-level Application Programming Interfaces (APIs)

- Nice to have experience in using some data science tools such as Data robot, Dataiku, Alteryx

When joining our team, you will experience:

- An international work environment, in which you can develop your talent and realize ideas and innovations within a competent team.

- Exposure to training and certification pathways for technical and functional skills from AWS, Snowflake, Informatica, and others

- Your own career path within Sanofi. Your professional and personal development will be supported purposefully.

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