Lead Data Scientists
We'd Love to See:Job Description
Lead Data Scientists for various and unanticipated worksites throughout the US (HQ: Chicago, IL). Lead the analysis, design and modification of statistical and economic data collection programs and the development/implementation of applications for disseminating our credit card client data. Lead analysts in the development of SQL and EMR/PySpark queries, and procedures, to extract data trends and relevant information from large data sources (millions of records). Design and develop business software and systems, using statistical analysis and mathematical models to predict and measure outcome and consequences of large financial datasets. Develop and use Python code to automate the production of statistical tables, figures and listings, which will assist in design and creation of submissions of electronic data (e.g. SQL data sets). Guide and oversee statistical and analytical data queries using SQL written by junior analysts. Develop and use SQL code and analysis including creation of new datasets, analysis, and empirical models. Develop mathematical and statistical theories and methods to collect, organize, interpret, and summarize numerical data. Identify relationships and statistical trends in data collection. Evaluate statistical methods and data modeling procedures used to obtain data. Review reports generated by junior team members. Supervise team members to assure that project goals created for statistical and mathematical data modeling are met from conception through execution. Provide technical software and statistical analysis guidance to analysts in interfacing statistical software solutions with the project’s parameters. Technical environment: R, Python, data automation, spline-based modeling, gam, mixed effect modeling, regularized modeling, time series modeling, creating customized machine learning algorithms, predictive models, survival models, look-alike models, clustering-based segmentation, and decision tree-based segmentation.
Master’s degree in Statistics, Analytics, Information Systems, related field plus 2 years of experience in job offered or in data science required. Required skills: large data sources (millions of records), SQL, R, Python, data automation, spline-based modeling, gam, mixed effect modeling, regularized modeling, time series modeling, creating customized machine learning algorithms, predictive models, survival models, look-alike models, clustering-based segmentation, and decision tree-based segmentation. 100% telecommuting permitted.