Real-World Evidence Data Scientist Job at Sanofi-Aventis Deutschland GmbH (Shanghai)

Medical - Real-World Evidence Data Scientist

To supervise and provide inputs to data management and statistical analyses for ...

Location

China , Beijing

Salary:

Not provided

Sanofi-Aventis Deutschland GmbH

Expiration Date

Until further notice

Requirements

Master degree in biostatistics/statistics, mathematics, epidemiology or relevant fields
At least 2 years of working experience preferable on observational RWS
Strong analytic skills of analyzing real-world data (including big electronic medical datasets)
Proficient in using statistical software (SAS/R/Python)
SAP writing experience
Ability to work effectively in a multi-cultural context as a good team member
Great potential/Capability to provide statistical leadership to cross-functional teams at the study level
Effective English communication skills in relating to colleagues and associates both inside and outside the organization
Ability to communicate in a credible and confident manner

Job Responsibility

Supervise and provide inputs to data management and statistical analyses for outsourced real-world studies (RWS)
Take a leading statistical role for RWS with in-house datasets
Interact with CRO to supervise and provide inputs to data management and statistical analyses and ensure timeliness and quality of statistical deliverables
Advise internal Medical team on study design, data management, statistical analysis, interpretation of statistical results, and publications
Perform programming and analytical activities for data cleaning and statistical deliverables in post-hoc analyses
Align with stakeholders on planning, delivering and communicating statistical analyses, data presentations, scientific reports, and publications
Comply with all statistics and quality processes and standards
Continuously assess the growth and accessibility of external real-world data assets, evaluate data quality and fitness-for-purpose, and develop compliant and efficient engagement models with data providers
Perform other duties, as assigned

Senior Manager, MED Oncology RWE/Epi Scientist

The Senior Manager, Oncology, position within Medical Evidence Development (MED)...

Location

United Kingdom , Walton Oaks

Salary:

Not provided

Pfizer

Expiration Date

Until further notice

Requirements

PhD in Epidemiology, Statistics/Biostatistics, Health Outcomes Research, Quantitative Methods, Public Health, Health Economics, or Other Biological Science fields with a substantial quantitative component and at least 1 years of relevant experience in the pharmaceutical, academic and/or medical environment
or, MPH or another relevant Master’s degree and at least 5 years of experience in the pharmaceutical, academic and/or medical environment, at least 1 of which were in the pharmaceutical industry
Demonstrated strong quantitative skills and methods expertise to generate rapid insights from real-world / observational data source
Demonstrated strong technical writing skills and oral presentation skills with a track-record of publishing in peer-reviewed journals and presenting at medical/scientific conferences
Demonstrated ability to convert complex analysis into meaningful insights with data visualization and presentation tools and able to manipulate and analyze complex structured and unstructured data from multiple real world evidence sources
Ability to work under pressure with a high level of autonomy/leadership on research projects and collaborate with multiple partners in a matrixed environment
Knowledgeable of the external regulatory environment for real-world evidence and maintains awareness of scientific developments in epidemiology, medicine, and technology (e.g., artificial intelligence)

Job Responsibility

Synthesizing the literature and contributing to the design, conduct and reporting of global epidemiologic research studies on Pfizer I&I products
Accountable for the quality, timeliness, and efficiency of all RWE/Epi deliverables in assigned product/disease area
Maintain an internal network of Pfizer stakeholders to cultivate innovation, cross-functional collaboration, and identify new opportunities for RWE/Epi to increase the value of Pfizer assets
Develop external partnerships to leverage data resources and collaboration on high priority global studies
Authoring and reviewing study protocols, reports, and presentations, as well as communication in writing and presentations to internal stakeholders, regulatory authorities, and medical professionals
Responsible for non-study deliverables such as RWE insights, epidemiology literature reviews, regulatory responses, and department initiatives
Identifying, designing and supporting or leading real-world evidence studies of disease epidemiology and effectiveness as part of the global cross-functional Integrated Evidence Plan
Maintain knowledge and awareness of internal and external data resources and identify appropriate studies for addressing questions of interest
Partner with Chief Medical Office colleagues to address asset team evidence needs and support global regulatory submissions to the FDA, EMA and other agencies
Deliver rapid insights from real-world, observational data source

Fulltime

New

Clinical Real World Data Scientist

The Clinical RWD Scientist is a critical role within the Data Assessment Center ...

Location

Canada , Toronto

Salary:

108900.00 - 157300.00 CAD / Year

Sanofi-Aventis Deutschland GmbH

Expiration Date

June 12, 2026

Requirements

Advanced degree (Master's or PhD) in Epidemiology, Biostatistics, Health Informatics, Health Economics, Pharmacoepidemiology, or a closely related quantitative discipline
Minimum 4-5 years for Master’s degree holder or 2-4 years for Doctoral degree holder of relevant experience in real-world data, commercial analytics, real-world evidence, health outcomes research, fit-for-purpose feasibility assessment, data quality assessment or a related field within the pharmaceutical, biotech, or health technology industry
Experience in predictive modeling using RWD to identify at risk patient populations with a publication record in peer-review journals
Experience in patient & healthcare provider segmentation to inform Medical and Commercial strategy
Demonstrated expertise in epidemiological study design and statistical methods such as propensity score matching, descriptive statistics, regression analysis, predictive modelling
Strong proficiency in statistical programming languages: SQL, Python, R, and/or SAS
Solid working knowledge of Snowflake for database querying and data extraction
Familiarity with medical coding systems: ICD-10, CPT, SNOMED CT, LOINC, RxNorm and experience/knowledge on OHDSI OMOP CDM standardized data model for healthcare data
Understanding of US EHR, claims, disease registry data, public health surveillance data as well as US healthcare billing system
Experience with AI coding tools such as Cursor, GitHub Copilot, Claude, LLM

Job Responsibility

Design and execute rigorous data assessment frameworks
Evaluating the fitness-for-purpose of real-world data (RWD) sources for insights or evidence generation across the enterprise
Support the development of reliable RWD Foundation and Products
Lead and execute feasibility assessments for RWD sources
Develop and apply structured data assessment frameworks to evaluate data quality dimensions
Assess the availability and representativeness of patient populations within RWD sources
Evaluate the feasibility of extracting structured and unstructured data elements from EHR systems
Document assessment outcomes in standardized feasibility reports and communicate findings clearly to cross-functional stakeholders
Identify and articulate limitations of RWD sources
Design methodologically sound recommendations & minimize misuse of RWD

What we offer

High-quality healthcare
Prevention and wellness programs
At least 14 weeks’ gender-neutral parental leave

Fulltime

Director, Global Real-World Evidence & Health Outcomes Scientist, Oncology

For drugs to be successful, there must be robust health outcomes data to support...

Location

United States , Philadelphia

Salary:

204000.00 - 340000.00 USD / Year

GSK

Expiration Date

Until further notice

Requirements

MSc, or equivalent in health outcomes, health economics, epidemiology, pharmacy, health or life sciences
3+ years of experience working in the pharmaceutical industry, preferably in a multi-national company
Experience in planning and delivering individual projects, managing budgets and working within a matrix setting
A history of designing a variety of RWE studies including prospective observational studies, cross-sectional and retrospective cohort studies, chart reviews, and database analyses
Proficiency in utilizing evidence for the development of HTA submissions, reimbursement and/or medical engagements
A track record of delivering robust payer evidence and credibility to engage meaningfully with external experts and leaders in the field
Expertise with the diversity and complexity of healthcare markets, health technology assessment agencies, and reimbursement decision making globally, in region and local markets
Experience in communicating technical and complex concepts and results to various audiences to impact decision-making
Experience in oncology.

Job Responsibility

Plan, design and execute multiple studies for a given asset and manage timelines, deliverables, and budget
Assure quality of deliverables, including review and sign off project specifications, protocols, data analysis plans, final study reports, abstracts, posters and manuscripts, in adherence to SOPs
Identify resources, references and analyses to inform scientific design and advise internal experts.(medical affairs, clinical, commercial/market access) and external experts as needed in support of the asset team
Translate needs for evidence into study concepts in alignment with strategic objectives and vision for the asset, e.g. development of study protocols and proposing innovative and cost-effective ways of developing and executing studies
Develop and maintain a good working knowledge of real-world data resources, existing partnerships and public initiatives and become the point person for select sources to advise on their suitability to address given research questions
Develop a deep understanding of customers’ needs, including clinicians and HTA requirements, and their acceptance of different types of evidence and impact of that evidence to their decision making
Collaborate with internal teams and participate in best practice sharing sessions across the non-interventional study organization
Build strong working relationships with stakeholder groups across medical, market access, R&D and commercial to ensure strategic alignment and optimal cross-functional collaboration and communication
Ensure key stakeholders, including TA aligned business leaders, are regularly updated on plans through periodic reporting
Develop excellent working relationships with external thought leaders to ensure appropriate methods and research agendas are applied, in accordance with GSK policies.

What we offer

Competitive base salary
Annual bonus based on company performance
Flexible working options available for most roles
Learning and career development
Access to healthcare & wellbeing programmes
Employee recognition programmes
Health care and other insurance benefits (for employee and family)
Retirement benefits
Paid holidays
Vacation

Fulltime

Pharma Data Science Consultant

As a Pharma Data Science Consultant, you will contribute to high-impact projects...

Location

Japan , Tokyo

Salary:

Not provided

Amaris Consulting

Expiration Date

Until further notice

Requirements

Proven experience as a Data Scientist with strong hands-on expertise in modeling and feature engineering
Mandatory background in the pharmaceutical or life sciences industry (pharma, biotech, CRO, healthcare analytics)
Strong knowledge of pharmaceutical data types: Clinical trial data, R&D or biomarker data, Real-world evidence (RWE), Commercial / sales / market access data
Proficiency in Python and/or R, with common data science libraries (pandas, NumPy, scikit-learn, etc.)
Experience working with structured and semi-structured datasets
Ability to work autonomously and provide data-driven recommendations
Strong analytical mindset and ability to bridge technical and business perspectives

Job Responsibility

Lead end-to-end data science projects, from problem definition to model deployment and interpretation of results
Advise stakeholders on data selection and prioritization, leveraging strong pharmaceutical domain knowledge
Perform advanced feature engineering on complex healthcare and pharmaceutical datasets
Develop, validate, and optimize machine learning and statistical models for pharma use cases
Translate business and scientific questions into robust data-driven solutions
Collaborate with data engineers, product owners, and business teams to ensure data and model relevance
Communicate data assumptions, methodologies, and results clearly to non-technical stakeholders
Contribute to best practices in data science, including documentation and reproducibility

What we offer

A dynamic international environment with opportunities to work on diverse projects
Strong career development path with training and internal mobility opportunities
Access to a global community of experts and knowledge-sharing initiatives
Involvement in innovative and high-impact projects within the life sciences sector

Fulltime

New

Scientist – Computational Audiology & Machine Learning

Do you want to improve the lives of millions with hearing loss? At Eriksholm Res...

Location

Denmark , Snekkersten

Salary:

Not provided

Demant

Expiration Date

May 17, 2026

Requirements

PhD degree (postdoctoral or equivalent level) in a relevant field, such as Applied Machine Learning, Mathematical Modeling, Computer Science, Data Science / Data Engineering, Biostatistics, Social Data Science, or Computational Audiology
Early-career researcher, typically within ~5 years since PhD degree
Experience with applied machine learning on real‑world data
Solid programming, statistical, data‑engineering skills and cloud-based platforms
Experience translating analytical methods into operational algorithms
Evidence of research output and/or impact appropriate to career stage (e.g., publications, software, data resources, clinical translation, or equivalent)
It is important that you can start onsite from day one

Job Responsibility

Develop machine‑learning models for translational audiological applications
Collaborate with stakeholders across research, development, and commercial teams
Work with data structures and modeling approaches between Eriksholm research data and Demant cloud-based storage platforms
Support R&D through scientific documentation and demonstrators
Publish in peer‑reviewed journals and present work at international audiology conferences

What we offer

Join a team of 35+ scientists, with a unique opportunity to work with world‑leading audiological research data
Work closely with Scientists, Research Audiologist and Researchers working with evidence studies across Eriksholm, and collaborate with clinicians, research institutions, and industry partners
A role with real societal impact, helping shape how hearing aids are fitted and personalized worldwide using large‑scale, real‑world hearing data
Strong support for scientific publication and international visibility
Scientific guidance from Eriksholm Principal Scientists, and line management from Sergi Rotger Griful, who focuses on ownership, direction, and helping people grow

Fulltime

Senior Data Scientist (NLP & LLMs)

Gong harnesses the power of AI to transform how revenue teams win. The Gong Reve...

Location

Israel , Tel Aviv

Salary:

Not provided

Gong

Expiration Date

Until further notice

Requirements

M.Sc. or Ph.D. in an exact science field or equivalent industry experience
5+ years of industry experience in data science/machine learning, including hands-on work with deep learning or large language models in real products
Practical LLM/NLP experience in building agentic workflows and NLP features end-to-end, from problem framing and data preparation to prompt/model design and production deployment
Deep familiarity with modern techniques, including RAG, fine-tuning, LLMs, as well as the evaluation frameworks required to benchmark them
Expert-level Python skills, including working with common data and ML libraries (e.g., pandas, NumPy, scikit-learn, PyTorch, Transformers, LangChain, or similar)
Proven track record designing and running large-scale experiments (e.g., offline benchmarks, prompt/model pipelines), and turning results into concrete decisions
Deep expertise in statistics and data analysis
Demonstrated skill in parsing unstructured, real-world data to uncover patterns and drive research strategy
Product mindset - Experience working with product managers and other stakeholders, with a strong sense for customer needs and value
Ability to break down ambiguous problems, propose alternatives, and help the team focus on what will move the needle for users and the business

Job Responsibility

The AI Product Lifecycle: Driving the roadmap from ideation to deployment, including defining success metrics and assessing technical feasibility for complex ML problems
Agentic Systems: Architecting the dynamic reasoning chains, tool-use logic, and multi-step workflows that power the Gong AI Assistant, enabling it to navigate complex tasks with intelligence and autonomy
Conversational Intelligence Strategy: Deep-diving into millions of calls and emails to extract key insights, ensuring our models capture the true intent and nuance of unstructured human interactions at scale
Model & Pipeline Engineering: Building robust Python environments to collect proprietary datasets, training models from scratch or fine-tuning them, and integrating LLMs into sophisticated pipelines that serve our global customer base
Temporal Context & Deal Dynamics: Developing methods to track intent and extract key insights across continuous, multi-month sales cycles, connecting the dots between multiple conversations and interactions across an entire deal journey
Applied AI Research & Implementation: Applying a versatile toolkit that includes advanced RAG, unsupervised clustering, fine-tuning custom models, and designing agentic workflows to build high-impact features
Intelligent Sales Assistance: Architecting the Gong AI Assistant to serve as a deep-research partner
you'll build models that answer complex user queries, perform deal-level research, and surface non-obvious insights that are traditionally hard to extract from raw dialogue
Technical Product Translation: Partnering closely with Product Managers to transform high-level product requirements into scalable ML solutions and production-ready model architectures
Global Sales Transformation: The features you build will directly empower thousands of companies and their sales teams, fundamentally changing how they interact with customers and close deals

Health Outcomes Scientist

The Health Economics & Outcomes Research (HEOR) Team is seeking to fill a full-t...

Location

Canada , Mississauga

Salary:

112000.00 - 162000.00 CAD / Year

GSK

Expiration Date

Until further notice

Requirements

Masters and/or Ph.D. in a field related to health economics and outcomes research, epidemiology, public health, or biostatistics
Experience leading epidemiological, health outcomes, or real-world observational research in Canada
Knowledge of health technology assessment processes and requirements in Canada
Experience with biostatistical methods, systematic reviews and meta-analyses
Knowledge of administrative and other Canadian databases that may be applied to address research questions relevant to GSK would be an asset
Strong project management skills
Strong written, verbal, and oral presentation skills

Job Responsibility

Lead, design and oversee the real-world evidence and outcomes research program to address data gaps relevant to reimbursement submissions, and to the launch of our innovative assets
Lead, design and adapt health economic models for submission to Canadian reimbursement authorities
Disseminate research findings through national and international conference presentations and submission of peer reviewed manuscripts within high impact journals
Collaborate with local and global GSK colleagues to define data gaps and develop evidence generation strategies to close these gaps
Provide expert consultation to cross functional team members on study design, statistical analysis, and potential impacts of new research
Support complex decision making and strategic planning across the therapeutic area-specific portfolio
Influence the global research program to address Canadian research needs, where appropriate
Cultivate relationships with external experts in outcomes research and explore ongoing opportunities for collaboration

What we offer

Competitive base salary
Annual bonus based on company performance
Flexible working options available for most roles
Learning and career development
Access to healthcare & wellbeing programmes
Employee recognition programmes

Fulltime

Real-World Evidence Data Scientist

Sanofi-Aventis Deutschland GmbH

Location:
China , Shanghai

Category:
IT - Software Development

Contract Type:
Not provided

Salary:

Job Description:

Job Responsibility:

Requirements:

Additional Information:

Job Posted:
March 13, 2026

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