Data Science Lead

Overview

The Data Science Lead will manage multiple small/medium projects or a large project for government and/or commercial clients, from the proposal stage through execution.  The Data Science Lead will help oversee the analytics of projects as part of a matrixed team and mentor others on the team. This is a highly cross-functional and collaborative senior role and requires a technical leader with strong program management, people management and business development skills.

Responsibilities

• Leads projects to develop custom analytics solutions using traditional statistical and modern data science methods for surveys, questionnaires, experiments, and other selected forms of research
• Provide leadership, management, and coordination of planning, data collection, analysis, performance measurement, quality assurance, and reporting to reliably capture the impact and effectiveness of the organization or program
• Coordinates with project managers to maintain schedule, budget, quality of deliverables and technical resources/staffing
• Serves as the main point of contact for clients on projects
• Responsible for managing and mentoring data science team
• Review technical data related to public health, healthcare and other data to prepare summaries, analyses, technical reports, manuscripts and presentations
• Design data management infrastructure and oversee management of databases, including codebooks, data dictionaries, and documentation
• Understands business requirements and works to create solutions meeting those requirements; Able to explain needs to relevant stakeholders
• Responsible for business development activities including executive networking, expanding current contracts, participating in capture activities for new work
• Serve as a writer/editor on proposals, help develop win themes, and lead the development of proposals
• Perform other related duties as required

Qualifications

• Master’s degree or higher in social sciences, quantitative discipline, or other relevant field
• 7 - 10 years’ work experience applied public health or healthcare analytics, with demonstrated experience in being the lead scientist in providing fast-paced analytics solutions for challenging research problems using statistical and/or data science approaches
• 3 – 5 years’ progressive experience leading multidisciplinary teams to meet multiple tight deadlines
• Experience working with healthcare quality measurement and claims data analysis
• Business development and proposal writing experience
• Experience designing and performing data science and statistical analysis using Pythion and/or R
• Thorough understanding of modern data science methodologies including, but not limited to classification algorithms, natural language processing, and assessment of biases and uncertainty in those methods
• Familiarity with statistical methods and research design such as linear, logistic, and conditional regression modeling, parametric and non-parametric statistics, cross-sectional and longitudinal data analysis, survival analysis, sample size calculation and power studies, surveillance and case-control study design and analysis, meta-analysis, and time series analysis
• Experienced with modern reproducible research methods including, but not limited to RMarkdown, Quarto, and/or Jupyter Notebooks
• Well-versed in Microsoft Office products and software to support quantitative analysis, qualitative analysis, information synthesis and reporting

PM18