Data Scientist I – II

Character Biosciences

. Implement models and analyses supporting drug discovery and development activities .

Posted 9/30/2026full-timeJersey City • New Jersey • United StatesJunior💰 $132,000 - $175,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in statistical and data science methods applied to real-world healthcare data, with a strong focus on developing quantitative biomarkers and disease progression models. Proficient in Python and R for data analysis, with experience in machine learning and biomedical imaging.

Highest-signal resume keywords

PhD In StatisticsStatistical And Data Science MethodsBiomedical Imaging Data AnalysisMachine Learning And Statistical MethodsReal-World Data Analysis

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Statistical MethodsData Science MethodsSurvival AnalysisMixed-Effects ModelingBayesian MethodsLongitudinal ModelsData Analysis Software DevelopmentQuantitative Biomarkers DevelopmentAnalytic Pipeline DevelopmentEncoder-Based Deep Learning Models

Soft Skills

Problem-Solving SkillsExcellent Communication SkillsTeam Collaboration

Tools & Technologies

PythonRAI ToolsOptical Coherence Tomography (OCT)MRICTHistopathology/IHCElectronic Medical Records (EMRs)

Industry Keywords

Drug DiscoveryClinical Trial DesignReal-World DataOphthalmology DataAMDGlaucoma

Tech Stack

Tools & technologies

Python

About the role

Key responsibilities & impact

Implement models and analyses supporting drug discovery and development activities
Develop quantitative biomarkers from imaging and phenotype data
Develop disease progression and time-to-event (survival) models
Conduct real-world-data analyses
Partner with clinical development and biostatistics teams on pre-specified and exploratory analyses
Support clinical trial design and interpretation using real-world data
Collaborate on cross-functional analyses with genomics, clinical research, and biology teams
Develop and implement improvements and extensions to the data platform
Build analytic pipeline modules and interactive analysis tools across AMD and glaucoma programs
Contribute to data and analytics strategic planning and roadmap
Contribute to scientific publications
Communicate data science work to internal and external stakeholders

Requirements

What you’ll need

PhD in Statistics, Data Science or a related technical field
1–3 years of professional experience applying statistical and data science methods to real-world healthcare data
Hands-on experience analyzing biomedical imaging data, ideally retinal imaging such as optical coherence tomography (OCT), fundus autofluorescence, or fundus photography
Experience with other imaging modalities such as MRI, CT, or histopathology/IHC is relevant
Comfortable writing production-quality Python and/or R code
Experience leveraging modern AI tools to implement analyses
Deep knowledge of machine learning and statistical methods, including survival/time-to-event analysis, mixed-effects modeling, and Bayesian methods
Experience developing longitudinal models on biomedical data, particularly real-world data including electronic medical records (EMRs) and/or claims data
Experience developing and implementing data analysis software modules and tools as part of data pipelines and to enable interactive analysis
Strong problem-solving skills focused on using data to drive action and decision making
Excellent communication skills and ability to work cross-functionally in team-oriented environments
Applicants must be authorized to work in the United States
Preferred: Experience developing and deploying encoder-based deep learning models in production
Preferred: Experience with ophthalmology data, particularly clinical data related to AMD or Glaucoma

Benefits

Comp & perks

Equity
Medical insurance
Dental insurance
Vision insurance
401(k)
Accrued paid time off policy
Diversity, equity, and inclusion culture