This position utilizes data analysis, data mining, pattern analysis, data visualization, reporting, and data management skills. Supports projects under close supervision of senior data analysts or data scientists. Types of work include descriptive analytics, data query scripting, data analysis, data engineering, visualizations, and forecasting. Other responsibilities: Provides data insights for business problems that can be approached with analytics techniques to collect, explore, and extract insights from structured and unstructured data. Has basic expertise in the data science methods used to analyze data, and knowledge of data types, topics, and scientific challenges and approaches. Executes analytical procedures in the framework of a specific project work request. Modifies scripts or software applications to support data management, data extraction and data analysis as required. Contributes to the interpretation of data analysis and to writing reports. May help customers understand the data set and provide training and suggestions for improvement on the data request. Leverages communication and interpersonal skills and works with subject matter experts Presents findings in easy to understand terms for the business or clinical practice.

Bachelor's degree in a domain-relevant field such as engineering, mathematics, computer science, statistics, physics, data science, health science, or another analytical/quantitative field. Ability to develop predictive models to address various business problems through leveraging advanced statistical modeling, machine learning, or data mining techniques, is preferred. Demonstrated application of several problem-solving methodologies, planning techniques, continuous improvement methods, and analytical tools and methodologies (e.g. machine learning, statistical packages, modeling, etc.) is required. Incumbent must stay current on healthcare trends and enterprise changes. Interpersonal skills and time management skills are required. Requires strong analytical skills and a commitment to customer service.

Preferred Qualifications The preferred qualifications are a guide to the skills and experiences that would be beneficial for the work you will engage in. We do not expect you to possess every qualification listed, and we encourage you to apply if you meet a subset of the following criteria: 

• Knowledge and experience in multiple programming and domain-specific languages (we primarily use Python, R, SQL, and Linux/Unix scripting) 
• Practical experience with reproducible research and version control systems like git, ensuring the maintainability and scalability of code bases 
• Experience with deep learning frameworks (e.g., PyTorch or TensorFlow) to implement various model types (e.g., CNNs, LSTMs, RNNs, object detection models) 
• Desire to bring new ideas to the team, the ability to work independently and continue learning in the rapidly evolving field of AI 
• Excellent communication skills, including technical writing and formal presentations 
• Experience in processing and analyzing/modeling time series, waveform, and image data 
• Familiarity with cloud computing ecosystems and their foundational technologies (e.g., virtualization, Docker, storage solutions, horizontal scaling) 
• Experience in developing proof of concept APIs/Applications utilizing Python or R frameworks (e.g., Dash, Streamlit, FastAPI, Flask, R Shiny, and Plumber) 
• Basic understanding of traditional statistics (e.g., experimental design, regressions, significance tests, confidence intervals, p-values)