Remote Associate Data Scientist

Summary

Join Allergan Data Labs as an Associate Data Scientist to contribute to the growth of the medical aesthetics business by working on technical problems and collaborating with stakeholders. The role involves data analysis, machine learning, and AI model design, deployment, and monitoring.

Responsibilities

• Work with cross-functional partners to understand & document business requirements including objectives, estimated costs & benefits, inputs, accuracy, latency, scale, and governance constraints
• Collaborate with Data Engineers, Software Engineers, and other business partners to identify, gather, cleanse, and organize data sets needed for analyses & modeling projects
• Perform exploratory data analyses using appropriate techniques (descriptive statistics, visual analytics, clustering, transformations, etc.) to understand, distill, and communicate the information content of data sets, and to extract features that are appropriate for formulation of metrics or as inputs to data models
• With guidance from seasoned Data Scientists, participate in inferential, predictive, prescriptive, causal, and other statistical analyses including hypothesis testing & forecasting to answer business questions, improve customer engagement, and drive business growth
• Assist seasoned Data Scientists to design, train, and evaluate machine learning and AI models while adhering to best practices including model selection, validation, bias/variance tuning, performance assessment, sensitivity analysis, dimensionality reduction, etc
• Collaborate with seasoned Data Scientists & Machine Learning Engineers to design and implement machine learning & AI models as scalable & robust solutions that can be deployed into production at scale, and help develop monitoring metrics to detect non-stationary behavior, anomalies, and degradation in production
• Follow our governance & development standards, including processes & frameworks for logging experiments, code & model quality standards, documentation, and source controlling artifacts
• Clearly document & present your work and informational materials at the appropriate level of detail to your team & business partners
• Maintain sharp professional knowledge & skills, and stay abreast of new developments in data science, machine learning, & AI
• Generate intellectual property and business ideas that could generate value for the company, such as new use cases and approaches to using data