• Data Scientist

    Job Location US-NY-New York
    Posted Date 3 weeks ago(6/25/2018 3:02 PM)
    Job ID
    2017-13234
    Category
    Market Research & Analytics
  • Overview

    Medscape, a division of WebMD, develops and hosts physician portals and related mobile applications that make it easier for physicians and healthcare professionals to access clinical reference sources, stay abreast of the latest clinical information, learn about new treatment options, earn continuing medical education credits and communicate with peers.  

     

    All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or veteran status

    Responsibilities

    The Data Scientist, Outcomes Research for Medscape Education will determine plans for research and execute statistical analyses to demonstrate the value of Medscape Education programs to funders and the education enterprise. The ideal candidate has a high degree of technological, statistical, and analytical skills, and is collaborative, creative, and curious and has the ability to recognize and solve problems independently. The Data Scientist, Outcomes Research will utilize data captured from online surveys, electronic medical records, and data purchased from other suppliers to help determine educational needs and inform strategic planning, as well as measure the impact of our educational interventions on learners and patients. The position will work independently and collaboratively with internal and external stakeholders and must be able to execute, understand, and report the results, including summary statements and data visualization methods

    Support of Medscape education programs
    • Partner with Sales and Educational Planning and Evaluation departments to independently establish research aims/designs, statistical analysis plans, and data extraction parameters that are a practical and visionary uses of available data
    • Execute research projects by:
    o Organizing and cleaning data with the objective of constructing analytical files
    o Performing programming, statistical analyses and/or modeling
    • Performing multiple qualitative and quantitative statistical analyses (bivariate and multivariate analyses, logistic regression analysis, chi square, p value), and specifically effect size calculations (Cramer’s V, Cohen’s d)
    • Interpreting, synthesizing, and analyzing data
    • Preparing reports with descriptive statistics, graphs, tables and figures using the appropriate software tools to visually present the data
    • Recognizing and providing actionable recommendations and key findings (i.e. “the story behind the data”)
    • Communicating results to stakeholders demonstrating an understanding of the educational products and medical education industry
    • Track and report to management progress of projects, adjusting as necessary to meet business objectives
    o Serve as internal consultant to Sales, Clinical Strategy, and Editorial Team on best practices for data analytics, training needs, and resolution of challenges, as needed/requested
    • Ability to explain statistics and display data in a way that makes it possible for novices to understand
    • Contribute to manuscript and grant development by documenting data management and analysis and helping to draft explanations of methodology
    • Take ownership of managing internal ad-hoc reporting requests and various internal process improvement initiatives
    • Independently recognize when elements of data are inconsistent with prior findings or expectations, and initiate discussion / raise questions
    • Maintain friendly and productive relationships with internal and external stakeholders
    • Author/co-author posters/presentations to disseminate research results at professional conferences and in manuscripts

    Qualifications

    • Bachelor's degree in qualitative/quantitative statistics, biostatistics, economics, sociology, public health, education, epidemiology or a relevant discipline preferred or equivalent years of experience.
    • Minimum of 5 years’ relevant work experience; medical education, online or healthcare data experience preferred.
    • Hands-on experience with R programming language and other tools such as SPSS and SAS, as well as data visualization tools
    • High degree of proficiency in Microsoft Office suite (PowerPoint, Excel, Word, Outlook); Ability to learn/use cloud-based software systems (e.g. Workfront, End Note, Box, SharePoint, Sales Force)
    • Demonstrated experience with basic bivariate and multivariate analyses, logistic regression analysis, chi square, p value), and specifically effect size calculations (Cramer’s V, Cohen’s d)
    • Experience designing statistical analysis plans and methodological strategies for prospective and retrospective studies; candidates with extensive appropriate experience preferred
    • Work experience and a sophisticated knowledge of techniques such as data merging, collapsing, manipulating to construct analytical files
    • Work experience and a sophisticated knowledge of large cross-sectional and/or longitudinal data sources
    • Excellent time management and organizational skills, with the ability to efficiently work on multiple tasks simultaneously in a highly deadline-driven environment, while taking into consideration stakeholders based across multiple time zones
    • Ability to work independently and in group setting
    • Demonstrable critical thinking and problem-solving skills, and high degree of initiative
    • Exceptional focus on accuracy, attention to detail and consistency of work
    • Must be able to communicate clearly and effectively
    • Positive attitude/very high energy with a willingness to accept varied assignments
    Preferred Qualifications
    • Graduate degree preferred
    • Experience in creating and assessing the impact of online or distant education
    • Strong knowledge of statistical data modeling, including descriptive and predictive modeling, epidemiological forecasting and population projections.
    • Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.
    • Working knowledge of data visualization tool such as Tableau
    • It is strongly preferable for the candidate to live in commuting distance to New York City and work out of our NYC office