FAQs
What type of data will the Data Scientist be working with?
The Data Scientist will be working primarily with omics data, including single-cell gene expression analysis.
What qualifications are required for this position?
An advanced degree (MSc or PhD) in Bioinformatics, Computational Biology, Data Science, or a related field is required, along with 2 years of industry experience in scaling systems and handling real, customer data.
What coding languages or tools should the candidate be proficient in?
While the job description does not specify particular languages or tools, candidates should have a strong understanding of machine learning, computational methods for bioinformatics, and programming languages typically used in data science (e.g., Python, R).
Is prior experience with machine learning mandatory for this role?
Yes, a deep understanding of machine learning and artificial intelligence is required, as the role involves developing, training, and testing machine learning models.
Are there opportunities for career advancement within the company?
Yes, the company emphasizes the potential for growth in your career, offering countless opportunities for promotions or lateral moves, both at home and internationally.
Will the Data Scientist be required to train non-technical staff?
Yes, the position requires the ability to communicate complex data insights to non-technical stakeholders.
What benefits are offered to employees?
Employees receive a thoughtful rewards package that includes high-quality healthcare, prevention and wellness programs, and at least 14 weeks of gender-neutral parental leave.
Is the company committed to diversity and inclusion?
Yes, Sanofi is an equal opportunity employer committed to attracting and retaining a diverse workforce and welcomes applications from all qualified candidates.
What is the work location for this Data Scientist position?
The position is located in Toronto, ON.
What are the main responsibilities of the Data Scientist?
Key responsibilities include providing expertise in omics data analysis, developing data processing algorithms, assisting in data interpretation, collaborating with data engineers, and contributing to data visualization strategies.