Data Science Technical Lead M/F

Job description

Data Science Technical Lead

The Technical Lead will work on challenging analytics projects and collaborate with Data Science leads, Data Management leads and ITS to adjust Sanofi’s Data Science practices and develop new solutions. Challenges will be identified from hands-on project responsibilities, as well as developing strategies and solutions for the broader Real World Advanced Analytics team. Identifying the problem is only half the job; you will be relied on to identify technical and methodological gaps in our solutions and seek to solve those gaps. You will provide expertise in data science and a broad range of technologies, and help us to develop, organize and launch projects that span analysis and engineering solutions.

RESPONSIBILITIES

·  Interact cross-functionally with a wide variety of data science leaders and teams, and work closely with Data Engineers/Managers and IT to identify opportunities to assess improvements for Real World analytics solutions.
·  Develop comprehensive understanding of Sanofi’s data science and data systems to support and integrate solutions for Advanced Analytics.
·  Prototype analysis pipelines iteratively to provide insights at scale.  Develop and implement metrics, advocating implementing and adoption of new solutions. 
·  Direct responsibilities to work with large datasets and solve difficult analysis problems, applying advanced analytical methods. Conduct end-to-end analyses, including data gathering and requirements specification, processing, analysis, ongoing deliverables, and presentations for business needs.
·  Develop optimal technical approaches for workflows, data handling, and complementary visualizations for advanced analytics. 
·  Project management for Advanced Analytics technical solutions.

REQUIREMENTS

·  Doctorate's degree in a quantitative or technical discipline (e.g., Statistics, Operations Research, Bioinformatics, Computational Biology, Computer Science, Mathematics, Engineering), plus 0-3 years of industry work experience.

OR

·  Master/Bachelor’s degree in a quantitative or technical discipline (e.g., Statistics, Bioinformatics, Computer Science, Engineering) or equivalent practical experience, plus 0-3 years of industry work experience.
·  Experience articulating business questions and implementing the improvement, or adoption, of new techniques (technology or analytical methods).
·  Highly developed project management skills.
·  High level of proficiency with analytics software (e.g., R, Python), database languages and computing environments/tools – e.g. Linux, AWS/GCP, shell scripting, and git.
·  Experience with statistical and data mining techniques (such as boosting, generalized linear models/regression, random forests, trees, and social network analysis).
·  Experience working with machine learning techniques, such as artificial neural networks, clustering, and decision tree learning.

Additional Desired Skills:

·  Experience in developing data processing workflow scheduling and monitoring, devops (e.g. basic pipelines, DAGs, multi-project, parent child using pySpark, Airflow, CI/CD using GitLab) including reading data from external sources, merge data, perform data enrichment and load in to target data destinations.
·  Experience with elements of knowledge management e.g. Ontologies, Knowledge Graphs, Master Data Management, etc.
·  Experience with various Application Programming Interfaces (APIs).

At Sanofi diversity and inclusion is foundational to how we operate and embedded in our Core Values. We recognize to truly tap into the richness diversity brings we must lead with inclusion and have a workplace where those differences can thrive and be leveraged to empower the lives of our colleagues, patients and customers. We respect and celebrate the diversity of our people, their backgrounds and experiences and provide equal opportunity for all.

As part of its diversity commitment, Sanofi is welcoming and integrating people with disabilities.