Snaplogic Developer - India - SourceBae

Description

We are looking for a seasoned professional with expertise in designing predictive demand forecasting models specifically tailored for the healthcare sector. This individual possesses extensive experience in leveraging data analytics, statistical modeling, historical data, and industry-specific insights to develop accurate and effective forecasting models that anticipate demand patterns for products and services within healthcare organizations.

Technical Skillsets:

∙Demonstrated proficiency in statistical analysis and modeling techniques, including time

series analysis, and regression analysis.

∙Advanced knowledge of programming languages commonly used in data analysis and

modeling, such as Python, R, or SQL.

∙Experience with data manipulation and cleansing techniques to ensure data quality and

integrity for accurate modeling.

∙Familiarity with data visualization tools and techniques to communicate insights

effectively, such as Tableau or Power BI.

∙Strong understanding of healthcare data sources and databases, including claims data,

epidemiology, demographic information, and administrative datasets.

∙Ability to determine appropriate data sets and features for input into demand forecasting

models, considering factors such as data availability, relevance, and predictive power.

∙Knowledge of forecasting software and tools tailored for healthcare applications.

∙Exposure to machine learning algorithms is a nice to have.

Job Responsibilities:

∙Collaborate with stakeholders to understand business requirements and objectives for

demand forecasting within healthcare organizations.

∙Design and develop predictive models to forecast demand for healthcare services,

procedures, or resources based on historical data and relevant variables.

∙Utilize advanced statistical analysis to analyze complex healthcare and related data sets to

identify predictive patterns and trends.

∙Evaluate model performance and accuracy using appropriate metrics and validation

techniques, and iteratively refine models as needed.

∙Work closely with data engineers and analysts to extract, transform, and load (ETL) data

from multiple sources for modeling purposes.

∙Communicate findings and insights from demand forecasting models to key stakeholders.

∙Understand how emerging trends and best practices in healthcare analytics and demand

forecasting contribute to the continuous improvement of modeling methodologies.