• Location: Budapest
• Flexible working: 60% home, 40% office
• Job type: Permanent, Full-time

About the job

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.

Our Hubs are a crucial part of how we innovate, improving performance across every Sanofi department and providing a springboard for the amazing work we do. Build a career and you can be part of transforming our business while helping to change millions of lives. Ready? As Real-World Evidence Data Scientist within our Budapest Hub, you’ll be responsible for the management and analysis of real-world data in evidence and insight generation projects for the General Medicines portfolio and support the Real-World Evidence Data Science Analytics Lead in the development of advanced analytics solutions.  You will be accountable for the high-quality and timely delivery of real-world data analyses prioritized in the global RWD&ES strategic roadmap, executing advanced analytics projects and delivering data analyses for different stages of a study. You will work 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 business growth.

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, statistics, text-mining/NLP, forecasting and optimization to multiple analytics projects to transform data into meaningful and actionable insights and evidence. Be 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.
• Collaborate with internal or external experts and departments to secure the completion of analyses to the highest scientific rigor and standards. 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.
• Provide clear explanations on analysis outputs to support 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.
• Support GenMed medical gaps within the Global Integrated Evidence Generation Plans (IEGP)

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:

• Minimum 3 years of relevant experience
• Advanced 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.
• 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, statistical modelling, causal inference methods and knowledge of advanced artistical techniques (e.g GAMs, machine learning, deep learning).
• Experience working in multiple therapeutic areas (transplant, type 1/2 diabetes or cardiovascular is prefereed) and 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). 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 tell stories with data and knowledge of complex visualization techniques preferred.
• Proven experience in managing multiple analytic projects concurrently.

Languages: Fluency in spoken and written business English is mandatory.

Why choose us?