Karna, LLC is seeking a Data Scientist II who will collect and analyze statistics and information from multiple sources to spot trends and gain insights to improve public health, develop algorithms, services, and visualizations for dashboards, and communicate informed conclusions and recommendations to clients and colleagues

• Contributes to development of custom analytics solutions using traditional statistical methods for surveys, questionnaires, experiments, and other selected forms of research
• Contributes to projects using modern data science methods, such as Machine Learning (ML), Natural Language Processing (NLP), and Artificial Intelligence (AI) to address non-traditional quantitative analysis needs and process big data
• Contributes to process improvement; Contributes to strong on-project performance
• Contributes to assignments under general supervision; Creates effective estimates of the level of effort required to complete tasks;
• Collaborate with client staff and colleagues to select the appropriate research design and conduct the appropriate analysis
• Able to understand business requirements and work to create solutions meeting those requirements; Able to explain needs to relevant stakeholders
• Manage databases, including codebooks, data dictionaries and documentation
• Implements Karna Analytics Standards and follows software development life cycle
• Communicate the results of analyses orally and in writing to scientific and non-scientific audiences
• Reviews technical work of peers in areas of expertise
• May train staff including statisticians and data scientists to assist with the design, collection, and analysis of data. This includes assigning and reviewing the data coding, computer programming, and other aspects of data management and analysis performed by other team members. 
• May participate on internal and external committees and workgroups related to areas of expertise

• BA/BS required, Masters/PhD preferred in quantitative discipline or related 
• Minimum of 3 years of professional experience performing data science and statistical analysis using Python and/or R
• Individual contributor with self-accountability; Owns own processes and tasks; Keeps leaders informed
• Works well with teams and individuals
• 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 T linear, logistic, and conditional regression modeling, parametric and non-parametric statistics, cross-sectional and longitudinal data analysis, survival analysis, sample size calculation and determination, surveillance and case-control study design and analysis, meta-analysis, and time series analysis
• Proficient in word processing and presentation development, primarily in Microsoft Office
• Experienced with modern reproducible research methods including, but not limited to RMarkdown and/or Jupyter Notebooks
• Experienced with large, nationally representative datasets
• Experienced with high volume, high variety, and high velocity data sources
• Experienced with data visualization