101658 - Associate Data Scientist
Summary
Associate Data Scientist at Henry Ford Health partnering with business users, analysts, and data engineers to build analytic and machine learning models from varied data sources. Day-to-day work involves extracting and transforming data with Python/R/SAS and SQL, applying statistical and ML algorithms, and presenting results via tools like Tableau or Power BI.
As an Associate Data Scientist, you will assist the Data Scientist and other business analysts with working with business users to fully understand their needs for data science solutions. You will work with a variety of data sources, both internal and external, big and small, structured and unstructured formats to build analytic models utilizing machine learning techniques. To achieve this, you will partner with the IT group to ensure that the data is sourced from the right location for data science model building. You will participate in the development of project deliverables, especially documentation, for data science deliverables. You'll be part of a team environment and interact with various other roles such as data engineers, business analysts and others. An ideal candidate for this position enjoys solving analytical problems and developing cutting edge solutions to business problems. The data scientist should also be skilled at extracting, transforming, and analyzing data using a variety of common analytical tools and statistical techniques. The Data Scientist should be able to present findings in a compelling manner to both a business and non-technical audience. The position requires a team player that is eager to continue to learn and evolve with business needs and changes in the data and business environment.
EDUCATION AND EXPERIENCE:
- Must have an undergraduate (BS), Masters or postgraduate (MS/Ph.D.) degree in Statistics, Mathematics, Econometrics, Operations Research, Public Health, Epidemiology, Data Science or related degree. Masters a plus.
- Experience involving quantitative data analyses for problem solving in US Healthcare industry preferred. Experience with predictive, forecasting, and optimization problem solving using object-oriented programming language like Python, R or SAS preferred. Knowledge on common data science libraries (Pandas, Scikit-learn, os, etc.).
- Advanced SQL skills working with RDBMSs such as Oracle, SQL Server, etc.
- Experience working with data visualization tools or Data Visualization Designers in Tableau or Power BI. Also, experience with data visualization for analytic models in Rshiny, GGPlot, Qlik, Alteryx, Flask, etc. used to tell the data story to business users to foster adoption of analytic outputs created preferred.
- Skilled and experienced in analyzing data and have a broad understanding of core statistical and ML algorithms like multi-class classification, decision trees, support vector machine, random-forest, Gradient Boosting.
- Effective communication and story-telling skills to provide insights to business units.
- Energy and enthusiasm. Passion for learning and contributing to development.