ASSOCIATE DATA SCIENTIST ANALYST

Job Summary:
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.

Job Responsibilities:
-Types of work include descriptive analytics, data query scripting, data analysis, data engineering, visualizations, and forecasting.
-Provides data insights for business problems that can be approached with analytics techniques to collect, explore, and extract insights from structured and unstructured data.
-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.
-Leverages communication and interpersonal skills and works with subject matter experts Presents findings in easy to understand terms for the business or clinical practice.
-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.

Skills:

Required Skills & Experience:
-Has basic expertise in the data science methods used to analyze data, and knowledge of data types, topics, and scientific challenges and approaches.
-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.)
-Incumbent must stay current on healthcare trends and enterprise changes.
-Interpersonal skills and time management skills.
-Strong analytical skills and a commitment to customer service.

Preferred Skills & Experience:
-Ability to develop predictive models to address various business problems through leveraging advanced statistical modeling, machine learning, or data mining techniques.

Notes:

Scope:
-AI modeling for vascular surgery imaging studies

Skills:
-Programming: Python , SQL, R
-AI & Machine Learning: Machine Learning, Deep Learning, Generative AI, LLMs, Retrieval-Augmented Generation (RAG), Forecasting, Optimization, Anomaly Detection, Scikit-learn, TensorFlow, XGBoost, Supervised & Unsupervised Learning, Deep Learning, Neural Networks, LSTM Autoencoders, Time-Series Modeling, Predictive Modeling
-Analytics: Machine Learning, Predictive Modeling, Segmentation, Statistical Analysis, Time Series Forecasting, Model Governance