Sr. Manager, Data Scientist - Parsippany, NJ

Role Summary

Sr. Manager, Data Scientist oversees the design and execution of data science solutions to improve clinical trials and business operations. The role leads the development of standards, templates, and architecture for data science initiatives, providing matrix leadership to teams and aligning infrastructure with business and IT needs. You will collaborate with scientists, engineers, product managers and stakeholders to deliver high-quality, production-ready machine learning solutions.

Responsibilities

• Plays a key role in the ongoing continuous improvement of descriptive statistics, data engineering, model building and evaluation, prediction, visualization and automation for business use.
• Plays a lead role in development of team and department-level standards, tools and templates.
• Provides matrix leadership to small teams in the development and maintenance of data science processes and applications.
• Defines and designs the overall data science solution architecture for assigned groups or projects.
• Coordinates infrastructure requirements with the business and IT to support the data science solution architecture.
• Designs data science workflows for the assigned area, incorporating best practice statistical analysis, data engineering, automation and visualization, deep learning and other contemporary machine learning techniques, models and tools.
• Builds, implements, tests, deploys and maintains innovative data and Machine Learning solutions to improve clinical trials and other business operations.
• Performs statistical analysis of results to tune / refine Machine Learning models.
• Collaborates with scientists, engineers, product managers and other business stakeholders to design and implement software solutions.
• Uses Machine Learning best practices to ensure a high standard of quality for all deliverables.
• Creates and manages resource plans for assigned work. Identifies cross-project synergies to leverage efficiencies and ensure consistencies where appropriate.
• Ensures assigned work complies with established practices, policies and processes and any regulatory or other requirements.

Qualifications

• Required: PhD in computer science, engineering, information systems or related discipline with 2+ years‚Äô data science experience. PhD with 6+ years‚Äô data science experience is preferred OR MS in computer science or related discipline with 8+ years‚Äô data science or relevant quantitative experience OR BS in computer science or related discipline with 10+ years‚Äô relevant experience in data science.
• Preferred: An academic focus on Artificial Intelligence / Machine Learning.
• Significant experience leading data science projects and project teams with a minimum of 2 years‚Äô cross-functional project management or leadership experience.
• Significant experience in end-to-end data science techniques, including data engineering, statistical analysis, modeling, visualization, presentation and warehousing.
• Significant experience building Machine Learning models and libraries.
• Strong programming skills in key languages used by Data Science (e.g., Python, SQL) with proven capabilities to manipulate large and sophisticated datasets using distributed computing technologies.
• Significant experience engineering and architecting data lakes, data warehouses and big data storage and platforms on AWS.
• Significant experience working with modern high-performance columnar storage formats.
• Strong proficiencies in problem-solving, algorithm design and complexity analysis.
• Significant experience contributing to open-source projects.
• Experience training others in data science principles, practices and tools.
• A track record in publications within own field is strongly preferred.