As a Data Scientist III, you will be a strong individual contributor embedded in the Clinical Development analytics function. You will design and build sophisticated ML and AI solutions, conduct rigorous statistical analyses on clinical datasets, and collaborate closely with clinical, medical, and operational stakeholders to translate complex data into actionable insights.
Responsibilities
Design, develop, and deploy predictive modeling and data science solutions — including regression, clustering, survival analysis, time series forecasting, and Monte Carlo simulation — to address clinical development challenges.
Conduct rigorous statistical investigations and exploratory data analysis across clinical datasets including trial data, EHR/EMR, and real-world evidence (RWE).
Translate moderately ambiguous scientific or operational problems into structured, hypothesis-driven analytical frameworks spanning study feasibility, trial execution, and patient analytics.
Build and maintain data and analytics pipelines — contributing to pipeline design decisions and ensuring computational efficiency within established architectural patterns.
Partner with senior data scientists and engineering teams on data quality, pipeline reliability, and scalability improvements.
Requirements
Bachelor's in Data Science, Statistics, Biostatistics, Computer Science, or a related discipline
Master's in Data Science, Statistics, Biostatistics, Computer Science, or a related discipline
Ph.D. in Data Science, Statistics, Biostatistics, Computer Science, or a related discipline
Analyze the performance of highly quantitative Comprehensive Capital Analysis and Review (CCAR)/Dodd-Frank Act stress testing (DFAST) econometric stress loss forecasting models and support CCAR/DFAST Current Expected Credit Losses (CECL) quarterly and annual model performance reporting.
Compensation
$114,600 to $117,500
Responsibilities
Analyze the performance of CCAR/DFAST econometric stress loss forecasting models
Support countries and regions for CCAR/DFAST CECL quarterly and annual model performance reporting
Compare performances of different modeling suites for regulatory submission
Monitor model performance on quarterly basis by analyzing and summarizing back-testing results
Document modeling activities related to model development, model change, model monitoring and forecasting analysis
Requirements
Master’s degree in Quantitative Finance & Risk Management, Finance, Statistics, Mathematics, Economics, or related quantitative field
Bachelor’s degree in specified fields with 5 years of post-baccalaureate experience
Analyze and validate quantitative regulatory models for Citibank’s CCAR/DFAST and CECL programs, monitor model performance, and support regulatory submissions.
Compensation
Wage Range: $114,600 to $117,500
Responsibilities
Analyze performance of CCAR/DFAST econometric stress loss forecasting models
Support countries and regions for CCAR/DFAST CECL quarterly and annual model performance reporting
Compare performances of different modeling suites for regulatory submission
Use loss forecast modeling to provide diagnostics and enhance monitoring
Monitor model performance on a quarterly basis
Requirements
Master’s degree in Quantitative Finance & Risk Management, Finance, Statistics, Mathematics, Economics, or related quantitative field
Support clinical statistical modeling activities across ongoing clinical trials and drug development programs.
Compensation
The salary for this position is $57 USD hourly. All compensation will be determined commensurate with demonstrated experience.
Responsibilities
Support clinical statistical modeling activities across ongoing clinical trials and drug development programs
Assist in the design, development, and validation of statistical models used in clinical decision-making
Perform data analysis and exploratory statistical work using clinical trial datasets
Collaborate with cross-functional teams (Biostatistics, Clinical Pharmacology, Data Management) to support modeling deliverables
Help prepare documentation, reports, and visualizations summarizing modeling outputs and findings
Requirements
Currently enrolled in a PhD program in Statistics, Biostatistics, Applied Mathematics, Computer Science, Pharmacometrics, or a related quantitative field.
Nice to have: Strong foundation in statistical theory and methods
Nice to have: Excellent analytical and problem-solving skills
Nice to have: Strong written and verbal communication skills
Nice to have: Ability to work both independently and collaboratively within a team environment
Lead the development, implementation and operation of analytics to monitor generation performance and support asset reliability and maintenance planning.
Compensation
Competitive Salary *401k Savings plan w/ company matching * Pension plan * Paid time off* Paid Holiday time * Medical, Prescription Drug, & Dental Coverage *Tuition Assistance Program * Employee Assistance Program * Wellness Programs * On-site Fitness Centers * Bonus Plan and more!
Responsibilities
Lead the development, implementation and operation of Analytics to monitor generation performance
Lead the development of analytics using Asset Management and formal reliability engineering
Lead the vision for analytics at the generating fleet level
Lead development of fleet level analytics centrally located on Power BI
Lead development of analytics for the support of performance reporting
Requirements
Bachelor’s degree in Engineering, Data Science, Applied Mathematics or Statistics
The base pay for this position is $100,000.00 – $200,000.00
Responsibilities
Responsible for independently executing advanced quality data analytics and investigation activities
Lead cross-functional data-driven initiatives focused on quality improvement, risk reduction, process optimization, and regulatory compliance
Analyze large and complex datasets from CAPA, Complaints, Nonconformances, Supplier Quality, Manufacturing, and Post-Market Surveillance systems to identify trends, signals, and root causes
Develop innovative, practical, and compliant analytical solutions to address complex quality and operational challenges
Apply statistical methods, machine learning models, and predictive analytics to proactively detect emerging quality issues and support decision-making
Requirements
Bachelor's Degree in life sciences or engineering or an equivalent combination of education and work experience
Responsible for designing and executing evidence-synthesis, health economic models to demonstrate the value of AbbVie products and communicate findings to stakeholders.
Responsibilities
Develop core global Systematic Literature Reviews (SLR), Indirect Treatment Comparison (ITC) and Health Economic Models (HEM) for HTA, payer and other Access stakeholders
Support affiliates with local adaptation of Global Models
Coordinate data requirements across biostatistics and evidence generation functions
Contribute to development of ITCs and HEMs to inform pricing and commercial strategy
Share best practices across affiliates and cross-functional partners
Requirements
Advanced degree MS/MSc/Mphil/MPH in Health Economics, Epidemiology, Statistics, Biostatistics, Public Health, Econometrics, or other related field
Senior Data Scientist focused on operations research to improve care delivery workflows and capacity planning within a remote-first health tech company.
Compensation
The salary range for this role is $175,000 - $200,000 depending on geography and level of experience, plus equity and an annual bonus.
Responsibilities
Redesign care delivery workflows and staffing models
Analyze event data to identify time and capacity bottlenecks
Build capacity models using queueing theory
Design and execute experiments to test workflow changes
Develop performance metrics separating workload from skill
Requirements
Bachelor's degree in Computer Science, Industrial Engineering, Operations Research, or related field
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