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Bayesian Modeling Expert

Il y a 2 mois

Paris, Île-de-France Quinten Health Temps plein
Job Description

As a Bayesian Modeler at Quinten Health, you will be part of a dynamic team of statisticians and data scientists working closely with Project Managers and clients to drive the development of our activities in the healthcare sector.

Key Responsibilities
  • Develop Analytical Strategies: Propose innovative analytical approaches to address customer challenges and align with business needs.
  • Conduct Statistical Studies: Plan and execute statistical/modeling studies to achieve the highest degree of client satisfaction using appropriate techniques.
  • Implement Bayesian Inference: Initiate, drive, and implement novel methods for Bayesian inference, complex statistical models, and innovative trial designs.
  • Anticipate Technical Benefits and Risks: Identify and anticipate the technical benefits and risks associated with the analytical approach.
  • Collaborate with Clients: Actively participate in exchanges with the client and be a key player in the project, from its framing to the presentation of the results.
  • Provide Expertise: Provide expertise to support documentation and submission activities, explaining statistical methodologies, and interpreting analysis results.
  • Participate in Scientific Dissemination: Participate in scientific dissemination, such as abstracts, posters, manuscripts, and conferences.
  • Contribute to Business Development: Participate in business development activities, such as proposal writing.

In addition to your role as Bayesian Modeler in the project teams, you will also contribute to the evolution of skills and know-how of the company and actively participate in technology watch to anticipate technical and commercial opportunities.

Requirements
  • Master's Degree or PhD: A master's degree with a minimum of 6 years of experience or a PhD with a minimum of 3 years of experience in a related and relevant area (statistics, data science, mathematical modeling, biometrics, etc.).
  • Experience in Bayesian Statistics: Experience in Bayesian statistics and modeling, MCMC practice, Bayesian decision analysis, or simulation-based optimization.
  • Advanced Statistics: Experience in advanced statistics, including parametric and non-parametric analyses, mixed-effects models, predictive modeling, network meta-analysis, imputations, advanced survival analysis, multi-state modeling, time series, stochastic processes, machine learning, and model selection.
  • Programming Skills: Master Python and/or R programming.
  • Synthesis and Communication Skills: Synthesis and communication skills allowing you to argue technological choices and explain their risks and benefits.
  • Knowledge Transmission: An appetite for knowledge transmission and the ability to explain complex concepts to a non-expert audience.
  • Health Sector Experience: A strong appetite for the field of health; experience in the health sector is a plus.
  • Organizational and Rigorous Qualities: Organizational and rigorous qualities, and a taste for teamwork.
  • Language Skills: Comfortable in English, both oral and written.
  • Statistical and Machine Learning Libraries: Master statistical and machine learning libraries (sklearn/caret, pandas/data.Table, etc.).
  • Continuous Integration: Knowledge of continuous integration (Git versioning, unit tests).
  • Bayesian Software: Experience with Bayesian software such as Stan or PyMC3 is a plus.
  • Distributed Computing: Knowledge of distributed computing (parallelization and/or Spark) is a plus.