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

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

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

Observational Research Director

We are currently hiring for an Observational Research Director to support the ob...

Location

United States

Salary:

187271.15 - 253366.85 USD / Year

Amgen

Expiration Date

Until further notice

Requirements

Doctorate degree and 4 years of scientific experience
Master's degree and 8 years of scientific experience
Bachelor's degree and 10 years of scientific experience
Doctorate in Epidemiology or other subject with high observational research content
Experience in the design, execution, and analysis of observational research studies within Pharmaceutical or Public Health setting
Experience in research to support drug development
Experience in observational research project planning and management
Excellent verbal and writing communication and interpersonal skills
Experience working in multi-disciplinary teams

Job Responsibility

Lead a team of epidemiologists to conceptualize, design, conduct, analyze, interpret and publish observational research supporting drug development programs and regulatory submissions, investigating post-marketing safety and effectiveness
Effectively lead, develop, and mentor a team of scientists
Be the technical expert in a cross-functional team to: identify evidence needs
develop the RWE plan to support the product development and commercialization strategy
and develop, maintain and expand a portfolio of observational research activities to support these strategies
Design and execute studies to support evidence generation such as identifying appropriate patient populations, assessing disease burden and resource utilization, obtaining product registrations and label-expansions, meeting post-marketing requirements/commitments, and product differentiation
Find opportunities to substitute for and/or complement interventional studies to reduce time and cost of drug development
Influence cross-functional team members as to the appropriate use and timing of non-interventional research to answer high-priority strategic business questions
Leverage real-world data and CfOR analytic approaches to inform high-value business decisions for multiple stakeholders
Track business and functional priorities and align resources against those priorities

What we offer

Comprehensive employee benefits package, including a Retirement and Savings Plan with generous company contributions, group medical, dental and vision coverage, life and disability insurance, and flexible spending accounts
A discretionary annual bonus program, or for field sales representatives, a sales-based incentive plan
Stock-based long-term incentives
Award-winning time-off plans and bi-annual company-wide shutdowns
Flexible work models, including remote work arrangements, where possible

Fulltime

Biostatistical Programming Senior Manager

In this vital role you will provide operational and technical leadership for Rea...

Location

United Kingdom , Uxbridge; Cambridge

Salary:

Not provided

Amgen

Expiration Date

Until further notice

Requirements

Degree educated
Relevant statistical programming experience within life sciences, clinical development, or observational research
Experience leading people, projects, programs, or resource allocation activities within a programming environment
Experience working with real-world healthcare data, including healthcare claims and EHR databases
Strong programming expertise in SAS and SQL
Knowledge of observational research methods, drug development, and epidemiology principles
Strong communication, collaboration, and stakeholder management skills
Demonstrated leadership, problem-solving ability, innovation, and attention to detail
Experience with R and/or Python is preferred but not mandatory

Job Responsibility

Provide operational and technical leadership for Real-World Evidence (RWE) biostatistical programming within the Centre for Observational Research (CfOR)
Lead and develop programming teams, partnering closely with epidemiologists and cross-functional stakeholders across multiple time zones to deliver high-quality RWE from large healthcare data sources, including electronic health records (EHR) and healthcare claims databases
Oversee project delivery, resource planning, technical excellence, and compliance with departmental standards and processes to support regulatory, publication, and enterprise objectives
Leading and developing programming staff, including mentoring, workload planning, and performance oversight
Partnering with epidemiologists, RWE scientists, and programming leads to generate robust real-world evidence from healthcare data assets
Providing technical leadership and guidance in statistical programming methods, standards, and best practices
Managing programming activities, timelines, deliverables, and resource allocation across multiple projects and priorities
Ensuring programming activities comply with departmental standards, SOPs, quality expectations, and regulatory requirements
Authoring, reviewing, and approving programming plans, analysis dataset specifications, macros, and other key study documentation
Contributing to the development, validation, and execution of analysis datasets and outputs supporting regulatory submissions, publications, and scientific communications

What we offer

Vast opportunities to learn and move up and across our global organization
Diverse and inclusive community of belonging, where teammates are empowered to bring ideas to the table and act
Generous Total Rewards Plan comprising health, finance and wealth, work/life balance, and career benefits

Fulltime

Scientist, Biomarker Analysis

The Biomarker Analysis Scientist will play a critical role in advancing translat...

Location

India , Hyderabad

Salary:

Not provided

Amgen

Expiration Date

Until further notice

Requirements

Doctorate degree with 3+ years of relevant scientific experience
OR Master's degree with 5+ years of relevant scientific experience
OR Bachelor's degree with 7+ years of relevant scientific experience
PhD (or equivalent) in Bioinformatics, Computational Biology, Statistics, Applied Mathematics, Computer Science, Data Science, or a closely related quantitative discipline from a well-regarded institution
Demonstrated experience analyzing complex, large-scale biological and clinical datasets, including multi-modal and longitudinal data
Strong grounding in statistical modeling and methods (e.g., regression, mixed-effects models, multivariate methods, correlative and causal analysis, prognostic and predictive biomarker analysis frameworks)
Working knowledge of machine learning and AI methodologies, with practical experience applying them to biological or clinical data
Experience in clinical trial settings is strongly preferred
Familiarity with clinical biomarker platforms and data types, such as NGS, flow cytometry, IHC, immunoassays, imaging, and transcriptional profiling
Proficiency in R and Python and version control (e.g. gitlab), with evidence of writing clear, reproducible, and maintainable analytical code

Job Responsibility

Design, execute, and interpret biomarker and translational analyses to support clinical development programs, including target engagement & stratification, pharmacodynamic modeling, patient stratification, mechanism of action validation, indication selection, and benefit–risk assessments
Develop and apply robust analytical workflows for high-content, multi-modal clinical data, including bulk and single-cell genomics, transcriptomics, proteomics, metabolomics, epigenomics, spatial omics, imaging, and emerging assay modalities
Translate complex biological and clinical questions into quantitative analysis plans, statistical models, and computational frameworks that generate actionable insights
Integrate internal clinical trial data with external datasets (e.g., public omics resources, real-world data, literature-derived knowledge) to contextualize findings and inform program strategy
Contribute to portfolio-level analyses and cross-asset learnings through principled data mining, visualization, and knowledge discovery approaches
Partner closely with biologists, clinicians, assay scientists, and data engineering teams to ensure analytical rigor, data quality, and scientific relevance
Clearly communicate analytical approaches, assumptions, limitations, and conclusions to diverse audiences through written reports, presentations, and cross-functional forums
Operate effectively in a global, matrixed environment, including regular collaboration across time zones with US- and EU-based teams
Strategically leverage AI to enhance speed, accuracy and insightfulness of results, maximally integrating relevant findings in the public domain

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

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

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