Senior Data Scientist - Drug Utilization Forecasting

Senior Data Scientist - Drug Utilization Forecasting

This job is no longer open
POSITION SUMMARY:

• Identify opportunities to modernize an actuarial framework with data science model-based solutions.

• Determine analytical approaches and modeling techniques to evaluate scenarios and potential future outcomes.

• Develop complex algorithms and statistical predictive models.

• Extract qualitative and quantitative relationships (i.e., patterns, trends) from large amounts of data using statistical and data mining tools.

• Work alongside the data engineering team to assess data quality, clean and organize data, optimize data flow and organization of code, production, and scale models.

• Apply analytical rigor and statistical methods to analyze large amounts of data using advanced statistical techniques.

• Develop an advanced understanding of the current forecasting system, stakeholders, and work products, and identify opportunities for enhancements and support of new initiatives.

• Create a new system to measure the forecast accuracy of current systems.

REQUIRED QUALIFICATIONS:

    • 3 or more years of relevant analytic experience
    • 3 or more years of experience programming using R, Python, SQL
    • 3 or more years of experience with dimension reduction, machine learning, and statistical algorithms

PREFERRED QUALIFICATIONS:

    • Advanced knowledge level for SQL.
    • 3+ years of experience applying modern machine learning techniques to build predictive models for both classification and regression problems using python libraries such as sci-kit-learn, ml-lib, xgboost, Keras, etc.
    • 3+ years of experience with general linear models, including regression techniques, ensemble models, etc.
    • 3+ years of experience coding in Python, including PySpark, and Pandas.
    • Experience with time series forecasting and causal modeling techniques.
    • Knowledge of full model development life cycle including EDA, feature engineering, data visualization, model development and deployment, forecast accuracy, model monitoring, and model drift.
    • Experience with the pharmaceutical or other healthcare domains with large administrative claims datasets including their associated code sets, terminologies, and ontologies.
This job is no longer open
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