Real World Evidence Data Scientist
Bridgewater, NJ
Sanofi
Sanofi pushes scientific boundaries to develop breakthrough medicines and vaccines. We chase the miracles of science to improve people’s lives.Job Title: Real World Evidence Data Scientist
Location: US Remote
About the Job
The US Evidence and Data Feasibility Team in Specialty Care collaborates across functions to develop and implement real-world data strategies for evidence and insight generation projects for US Medical. Partnering with key stakeholders across Market Access, HEVA, Digital Acceleration, and Innovation Teams, as well as global brand teams. The team spearheads robust real-world evidence (RWE) strategies, RWD Analytics, to include sourcing appropriate data, crafting strategic RWE approaches, and supporting the conduct of impactful studies that transform information into insights and evidence to enhance patient care, inform regulatory and access decisions, and improve health outcomes.
The Real-World Evidence Data Scientist is responsible for the management and analysis of real-world data in evidence and insight generation projects for the Specialty Care portfolio and supports the Real-World Evidence Data Science Analytics Lead in the development of advanced analytics solutions. He/She will be accountable for the high-quality and timely delivery of real-world data analyses prioritized in the global real world data 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 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 advanced analytics and successfully applying advanced analytics methods to delivering innovative and competitive solutions for medical impact.
We are an innovative global healthcare company, committed to transforming the lives of people with immune challenges, rare diseases and blood disorders, cancers, and neurological disorders. From R&D to sales, our talented teams work together, revolutionizing treatment, continually improving products, understanding unmet needs, and connecting communities. We chase the miracles of science every single day, pursuing progress to make a real impact on millions of patients around the world.
Main Responsibilities:
Provide technical expertise for designing and delivering real-world data (RWD) studies, ensuring scientifically rigorous methods.
Identify analytical problems in real-world evidence (RWE) and develop data-driven solutions.
Serve as SME and drive utilization and scaling of data/insight tools and systems.
Design and implement data mining and statistical techniques for RWE datasets, ensuring data quality and integrity.
Develop and maintain programming macros/tools for efficient support, including their development, implementation, and upkeep.
Serve as SME for system upgrades, proposing and supporting system utilities.
Apply machine learning (ML) and artificial intelligence (AI) to extract insights, build predictive models, and align with future technology roadmaps.
Contribute to building a robust RWD/RWE environment, including statistical planning and promoting innovative solutions and operational excellence.
Collaborate with cross-functional teams to translate business needs into data analysis specifications and facilitate effective communication of insights.
Uphold best practices in data science, ensuring compliance with ethical standards and efficient documentation.
Stay current on industry advancements in AI/ML and promote their efficient use across teams.
Implement data visualization to communicate findings and contribute to developing data-driven healthcare solutions.
Maintain clear communication with stakeholders to ensure alignment, manage risks, and ensure smooth project progression.
About you
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 pharmaco-epidemiology, statistics, mathematics, computer science, or related field. PhD is preferred.
Experience:
Expert knowledge in RWE, pharmaco-epidemiology, health outcomes research, statistical methods, etc.
Experience in statistical programming SAS, R, Python or data base programming (SQL) is a must.
Experience working with routinely collected data (claims databases, electronic Specialty Care 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 respiratory, immunology and hematological therapeutic areas 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.
US Experience and exposure to the academic societies, ICDs and clinical practice guidelines is highly preferred.
Languages:
Fluency in spoken and written business English mandatory
Why Choose Us?
Bring the miracles of science to life alongside a supportive, future-focused team.
Discover endless opportunities to grow your talent and drive your career, whether it’s through a promotion or lateral move, at home or internationally.
Enjoy a thoughtful, well-crafted rewards package that recognizes your contribution and amplifies your impact.
Take good care of yourself and your family, with a wide range of health and wellbeing benefits including high-quality healthcare, prevention and wellness programs and at least 14 weeks’ gender-neutral parental leave.
The salary range for this position is $122,250.00 - $163,000.00 USD Annually. All compensation will be determined commensurate with demonstrated experience. Employees may be eligible to participate in Company employee benefit programs. Additional benefits information can be found through the link, www.benefits.sanofiusallwell.com
Sanofi Inc. and its U.S. affiliates are Equal Opportunity and Affirmative Action employers committed to a culturally diverse workforce. All qualified applicants will receive consideration for employment without regard to race; color; creed; religion; national origin; age; ancestry; nationality; marital, domestic partnership or civil union status; sex, gender, gender identity or expression; affectional or sexual orientation; disability; veteran or military status or liability for military status; domestic violence victim status; atypical cellular or blood trait; genetic information (including the refusal to submit to genetic testing) or any other characteristic protected by law.
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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, 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!
US and Puerto Rico Residents Only
Sanofi Inc. and its U.S. affiliates are Equal Opportunity and Affirmative Action employers committed to a culturally inclusive and diverse workforce. All qualified applicants will receive consideration for employment without regard to race; color; creed; religion; national origin; age; ancestry; nationality; natural or protective hairstyles; marital, domestic partnership or civil union status; sex, gender, gender identity or expression; affectional or sexual orientation; disability; veteran or military status or liability for military status; domestic violence victim status; atypical cellular or blood trait; genetic information (including the refusal to submit to genetic testing) or any other characteristic protected by law.
Tags: Bayesian Causal inference Computer Science Data analysis Data Mining Data quality Data visualization Deep Learning Machine Learning Mathematics NoSQL Pharma PhD Python R R&D Reinforcement Learning Research SAS Scala Snowflake SQL Statistics Testing Unsupervised Learning
Perks/benefits: Career development Competitive pay Equity / stock options Gear Health care Medical leave Parental leave Startup environment Team events Wellness
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