Real-World Evidence Data Scientist
Paris, France
Sanofi
Sanofi pushes scientific boundaries to develop breakthrough medicines and vaccines. We chase the miracles of science to improve people’s lives.Le contenu du poste est libellé en anglais car il nécessite de nombreuses interactions avec nos filiales à l’international, l'anglais étant la langue de travail.
This job offer is accessible to all, regardless of gender.
Job title: Real-World Evidence Data Scientist
- Grade: L4-1
- Hiring Manager: Enkeleida Nikai
- Location: Morristown, NJ
About the JobIn Sanofi General Medicines, we are dedicated to improving the day-to-day health of millions of patients around the world. Despite huge leaps forward in public health, even today, many patients still don’t receive the care they need.
Not only are we helping treat more patients today, we’re enabling the science that will deliver even better medicines tomorrow. We’re transforming our business and the way we engage with our customers to reverse the rapid global growth of chronic conditions such as diabetes, cardiovascular disease and transplant.
Powered by our scale and expertise, we seek to maximize reach and impact for our patients by strengthening healthcare partnerships, designing more comprehensive treatment solutions, digital health models and data-driven personalization and analytics, and putting Sanofi’s signature Play to Win practices into action.
Every day, we harness innovation to ensure we’re always one step ahead of our customers’ needs, bringing improved support—and hope—to patients the world over. With all of us playing our part, we’re poised to vastly expand our reach and elevate the standard of care for those battling chronic conditions everywhere.
The Real-World Data & Evidence Science (RWD&ES) team, in General Medicines Medical, serves as an end-to-end strategy and execution partner to solve business problems using real-world data. The team partners with medical, market access, health economics & value assessment (HEVA), and all cross-functional partners in the Global Brand Teams to lead end-to-end the strategy and execution of real-world evidence (RWE) strategies by identifying and sourcing fit-for-purpose data, developing robust RWE strategies and delivering timely RWE studies with strong impact for all our stakeholders including patients, physicians, payers and regulators. We are the team at the forefront of unlocking value from real-world data and translating data into insights and evidence to better understand patient needs, change the practice of medicine, inform regulatory and access decision-making and ultimately improve health outcomes.
The Real-World Evidence (RWE) Data Scientist is responsible for the management and analysis of RWE projects for the General Medicines portfolio and works closely with the RWE Data Science Analytics Lead in the development of advanced analytics solutions. He/She will be accountable for the high-quality and timely delivery of RWD analyses prioritized in the global RWD&ES strategic roadmap. The successful candidate will be responsible for executing advanced analytics projects and delivering data analyses for different stages of a study. This role works in close partnership with the Digital organization, Sanofi Global Hub (SBO) and The RW Data Science Analytics Lead to leverage expertise to the required standards according to defined processes. This is an important role in developing our capabilities in RWE advanced analytics and successfully applying advanced analytics methods to delivering innovative and competitive solutions for business growth.
We are an innovative global healthcare company with a focus on immunology that extends to innovation in diabetes and transplant medicine. Across different countries, our talented teams are determined to deliver a best-in-class customer experience using the best of digital, artificial intelligence and personal know-how. With a focus on immunology that extends to innovation in diabetes and transplant medicines, we pursue progress to make a real impact on millions of patients around the world.
Main Responsibilities:
Provide technical expertise for the design and delivery of studies using real world data; ensure scientifically rigorous methods are applied for addressing medical, economic and outcomes research questions
Effectively translate business requirements into data analysis specifications
Verify data source integrity and validity to ensure compliance to data and ethical standards deployed throughout the data transformation process
Apply data science expertise in machine learning, deep learning, artificial intelligence, text-mining/NLP, predictive modeling and optimization to multiple analytics projects to transform data into meaningful and actionable insights and evidence
Collaborate with other internal or external experts and departments as needed to secure the completion of analyses to the highest scientific rigor and standards
Provide clear explanations on analysis outputs to support appropriate interpretation of study results and/or insights that drive business decisions
Promote best practices and adhere to standards for data science processes, including documentation and code developments
Be a strong internal expert in data science while staying ahead of new methodological developments in the RWE Data Science field. Be an expert in advanced analytics and advise business leaders in machine learning, deep learning, text-mining/NLP, etc
Maintain up-to-date with industry practices and emerging technologies such as generative AI and test creative ways of offering AI solutions to enhance existing processes and solutions
Maintain timely communication and close alignment with team members, partners and stakeholders to ensure clear and timely visibility to the project progress and anticipation of challenges and risks
Accountable for supporting GenMed medical gaps within the Global Integrated Evidence Generation Plans (IEGP)
You are a self-starter who brings your energy, expertise and experience as well as takes an entrepreneurial approach to solving problems, have a growth mindset and are passionate about unleashing the power of real-world data with data science to improve health.
Education:
- Master’s degree in quantitative fields such as statistics, applied mathematics, computer science, or related field. PhD is preferred
Experience:
- Expert knowledge in RWE, pharmaco-epidemiology, health outcomes research, statistical methods, etc.
- Experience in R, Python or data base programming (SQL) is a must
- Experience working with routinely collected data (claims databases, electronic medical health records, registries and various structured and possibly unstructured sources in the healthcare sector within pharmaceutical company settings
- Demonstrated experience in the use of advanced analytics methods. Extensive experience in statistical modelling, causal inference methods (propensity scoring techniques, comparative effectiveness analysis, etc) and knowledge of advanced artistical techniques (e.g GAMs, machine learning, deep learning)
- Experience working in multiple therapeutic areas – experience in transplant, type 1/2 diabetes or cardiovascular highly preferred
- Experienced working in complex global matrix teams and with service providers requiring cross-functional collaboration and alignment
Soft skills:
- Strong sense of urgency, ownership and proactive attitude to deliver value to our brands
- Ability to adapt and communicate messages to a wide range of audiences at all levels (both scientific and commercial), inside and outside of the organization. Able to clearly articulate highly technical methods and results to diverse non-technical audiences to drive decision making
- Apply growth mindset to develop new skills or knowledge
Technical skills:
- Advanced programming and statistical computing software skills, expertise with core data science languages (predominantly Python, and nice to have R & Scala), experience working with Snowflake and other different database systems (such as SQL, NoSQL)
- Expertise within some of the following areas: supervised learning, unsupervised learning, deep learning, reinforcement learning, federated learning, time series forecasting, Bayesian statistics, optimization
- Expertise in RWE study designs and methodologies, including innovative techniques
- Ability to translate complex technical language into easy-to-understand communication with collaborators and stakeholders
- Ability to tell stories with data and knowledge of complex visualization techniques preferred
- Proven experience in managing multiple analytic projects concurrently
- Management of analytical activities of external service providers is highly preferred
Languages:
- Fluency in spoken and written business English mandatory
Better is out there. Better medications, better outcomes, better science. But progress doesn’t happen without people – people from different backgrounds, in different locations, doing different roles, all united by one thing: a desire to make miracles happen. So, let’s be those people.
At Sanofi, we provide equal opportunities to all regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, or gender identity.
Watch our ALL IN video and check out our Diversity Equity and Inclusion actions at sanofi.com!
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Pursue progress, discover extraordinaryBetter is out there. Better medications, better outcomes, better science. But progress doesn’t happen without people – people from different backgrounds, in different locations, doing different roles, all united by one thing: a desire to make miracles happen. So, let’s be those people.
At Sanofi, we provide equal opportunities to all regardless of race, colour, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, ability or gender identity.
Watch our ALL IN video and check out our Diversity Equity and Inclusion actions at sanofi.com!
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Bayesian Causal inference Computer Science CX Data analysis Deep Learning Economics Generative AI Machine Learning Mathematics NLP NoSQL Pharma PhD Predictive modeling Python R Reinforcement Learning Research Scala Snowflake SQL Statistics Unsupervised Learning
Perks/benefits: Career development Equity / stock options Health care Startup environment
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