Sanofi Business Operations is an internal Sanofi resource organization based in India and is setup to centralize processes and activities to support Specialty Care, Vaccines, General Medicines, CHC, CMO, and R&D, Data & Digital functions. Sanofi Business Operations strives to be a strategic and functional partner for tactical deliveries to Medical, HEVA, and Commercial organizations in Sanofi, Globally.

Main responsibilities:

Contribute to the growth of General Medicine's real-world evidence capability, including real world evidence (RWE) to support studies and projects across the franchises motivated by business needs; work closely with the Medical, Market Access, HEOR, and Commercial team to maximize the value of our portfolio of priority assets worldwide; unique opportunity for a data scientist and/or epidemiologist to join a motivated and experienced research team in an innovative working environment to address key tasks in health and social care surrounding CV disease and diabetes; work collaboratively to create high quality innovative analytical products, can benefit from a wealth of in-house databases, study platforms, and analytic tools, and from external partnerships with academic and governmental institutions.

People:
(1) Work together with RWE team to support projects across the franchises motivated by business needs
(2) Work closely with the Medical, Market Access, HEOR, and Commercial team to maximize the value of our portfolio of priority assets worldwide
(3) Work collaboratively within Medical and across functions, with clients and external collaborators
(4) Functionally reports to the Head of the Real-World Evidence team
Process:
(1) Work together and lead research analytical projects, including project conceptualization and design
(2) Lead analysis of healthcare data, including clinical trial datasets, transactional claims, and electronic health records, using established and novel statistical and analytical techniques
(3) Generate rapid response analyses for cross-functional stakeholders
(4) Lead or contribute to drafting and reviewing technical and study reports, manuscripts for publishing in high-impact peer-reviewed journals, and abstracts and presentations for international conferences
(5) Actively manage project activity and timelines
(6) Internally advise your colleagues in the Health Economics, Commercial, and Medical franchises on your areas of technical and research expertise as directed by your supervisor
(7) Communicate complex concepts and interpretation of analysis and findings to different audiences, including health economists, clinicians, policy makers, and health systems
(8) Represent the team at external meetings
(9) Validate and secure access to third-party healthcare data-sets
Customer:
(1) Deliver research and contributes to the RWE strategic direction for General Medicines

About you

Experience: 7 - 10 years in public health, biotechnology and/or pharmaceutical industry; Strong healthcare data analysis expertise, expertise in data analysis techniques, and good understanding of healthcare datasets (EHR, Claims, RCTs), and data structures; Expertise in use of statistical methods to investigate real-world problems (e.g., data modelling, time to event analysis); Advanced experience in preparing, analysing, and managing large healthcare datasets in interventional and/or non-interventional studies; Experienced in interpreting and presenting complex analyses and findings; Experienced in interpreting and presenting complex analyses and findings
Soft skills: Integrity; Analytic excellence; Excellent written and oral communication skills; ability to communicate complex topics and data results in a concise and precise manner; High level of self-awareness; Ability to cooperate cross-functionally; Problem-solving and creative thinking skills; Enjoys working independently, flexibly and as part of a team on multiple projects; Enthusiastic and professional approach to working with colleagues, clients, and external collaborators
Technical skills: R, Python, SQL, advanced Microsoft Excel using Visual Basic for Application, SAS Education: Masters or PhD in a quantitative subject (e.g., computer science, data science, statistics, mathematics, biostatistics, biomedical engineering, epidemiology) or equivalent combination of education, training, and experience
Languages: Excellent knowledge of English language (spoken and written)

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