Data Modeler II
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Data Modeler II with a contract length of "unknown," offering a pay rate of "unknown," located in a hybrid setup in Charlotte, North Carolina. Requires 5+ years of experience, expertise in predictive modeling, and proficiency in SAS, Python/R, and data analysis tools.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
-
🗓️ - Date discovered
August 21, 2025
🕒 - Project duration
Unknown
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🏝️ - Location type
Hybrid
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📄 - Contract type
W2 Contractor
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🔒 - Security clearance
Unknown
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📍 - Location detailed
North Carolina, United States
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🧠 - Skills detailed
#Data Extraction #Documentation #Python #ML (Machine Learning) #Databases #R #Statistics #Mathematics #AI (Artificial Intelligence) #"ETL (Extract #Transform #Load)" #SAS #Scala #Tableau #Data Analysis #Spark (Apache Spark) #Data Mining #Data Manipulation
Role description
Only W2 candidates // Hybrid // Charlotte, North Carolina
SUMMARY OF DAY TO DAY RESPONSIBILITIES:
• Data mining - making sense of some very large databases of credit risk related historical data by leveraging state of art statistical technics, such as machine learning and artificial intelligence algorithms
• Predictive credit risk modelling based on rigorous statistical analysis of historical data that will assist our key business partners achieve growth and profitability targets while maintaining acceptable levels of risk within our lending portfolios
• Assist in the validation and assessment of internally and third party developed predictive models, includes data extraction, data analysis, assisting in methodology development and documentation
• To develop and maintain expertise with lending, credit scoring, behavior scoring, portfolio management and industry trends
• To provide decision support, analytical, and statistical service through modeling and segmentation to help Lending BUs achieve business objectives.
This position provides excellent learning, working and career opportunities in a highly professional and motivated team environment, and exposure to a variety of high-paced and intensive modeling projects and to a variety of internal and external stakeholders
MUST HAVE:
• 5+ years of relevant working experience
• Sound knowledge in industry best practices in predictive modelling, including machine learning algorithms
• A university degree in quantitative discipline (Statistics, Mathematics, Computer mathematics, Econometrics, Operations Research); An advanced degree is an asset
• Proficiency in programing using statistical analysis tools, such as SAS, Python/R, Scala, Spark etc., in the context of data manipulation, data mining, statistical analysis, and predictive modelling;
• Proved to be a quick learner, strong problem-solving skills, ability to independently identify and solve problems in an effective and timely manner;
NICE TO HAVE
• Proficiency in dashboard building tools like Tableau.
Only W2 candidates // Hybrid // Charlotte, North Carolina
SUMMARY OF DAY TO DAY RESPONSIBILITIES:
• Data mining - making sense of some very large databases of credit risk related historical data by leveraging state of art statistical technics, such as machine learning and artificial intelligence algorithms
• Predictive credit risk modelling based on rigorous statistical analysis of historical data that will assist our key business partners achieve growth and profitability targets while maintaining acceptable levels of risk within our lending portfolios
• Assist in the validation and assessment of internally and third party developed predictive models, includes data extraction, data analysis, assisting in methodology development and documentation
• To develop and maintain expertise with lending, credit scoring, behavior scoring, portfolio management and industry trends
• To provide decision support, analytical, and statistical service through modeling and segmentation to help Lending BUs achieve business objectives.
This position provides excellent learning, working and career opportunities in a highly professional and motivated team environment, and exposure to a variety of high-paced and intensive modeling projects and to a variety of internal and external stakeholders
MUST HAVE:
• 5+ years of relevant working experience
• Sound knowledge in industry best practices in predictive modelling, including machine learning algorithms
• A university degree in quantitative discipline (Statistics, Mathematics, Computer mathematics, Econometrics, Operations Research); An advanced degree is an asset
• Proficiency in programing using statistical analysis tools, such as SAS, Python/R, Scala, Spark etc., in the context of data manipulation, data mining, statistical analysis, and predictive modelling;
• Proved to be a quick learner, strong problem-solving skills, ability to independently identify and solve problems in an effective and timely manner;
NICE TO HAVE
• Proficiency in dashboard building tools like Tableau.
