Data Modeler II

⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Data Modeler II with a 15-month contract in Charlotte, NC, paying from $53/hour. Requires 5+ years of experience in predictive modeling, proficiency in SAS, Python/R, and a quantitative degree. Hybrid work model.
🌎 - Country
United States
πŸ’± - Currency
$ USD
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πŸ’° - Day rate
424
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πŸ—“οΈ - Date discovered
August 21, 2025
πŸ•’ - Project duration
More than 6 months
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🏝️ - Location type
Hybrid
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πŸ“„ - Contract type
Unknown
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πŸ”’ - Security clearance
Unknown
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πŸ“ - Location detailed
Charlotte, NC
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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 #Data Analysis #Spark (Apache Spark) #Data Mining #Data Manipulation
Role description
Our client is a top financial institution with significant North American holdings.Β They have operations across most major verticals, including institutional & corporate, wealth management, private client, commercial banking, treasury, and retail banking. Introduction: Robertson is seeking a skilled Data Modeler to join our client. Contract Period: 15 months Pay Rate: Starting from $53 per hour Location: Charlotte, NC Location Type: Hybrid: 2 days onsite per week, moving to 4 days in Nov Business Hours:Β Monday to Friday; Core Business Hours Job Responsibilities: β€’ 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. β€’ 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. β€’ 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. β€’ To develop and maintain expertise with lending, credit scoring, behavior scoring, portfolio management and industry trends. β€’ To provide decision support, analytical, and statistical service through modeling and segmentation to help Lending BUs achieve business objectives. β€’ 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. Experience & Qualification Requirements: β€’ 5+ years of relevant working experience β€’ Sound knowledge in industry best practices in predictive modelling, including machine learning algorithms β€’ A university degree in quantitative discipline (Statistics, Mathematics, Computer mathematics, Econometrics, Operations Research); An advanced degree is an asset β€’ 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 β€’ Proved to be a quick learner, strong problem-solving skills, ability to independently identify and solve problems in an effective and timely manner β€’ β€’ β€’ β€’ ALL CANDIDATES MUST COMPLETE A FULL BACKGROUND CHECK AS PART OF THE APPLICATION PROCESS β€’ β€’ β€’ β€’ How to Apply: If you are a motivated professional looking to contribute to a leading team, please submit your resume outlining your qualifications and experience relevant to this role. Robertson & the clients we represent, value diversity and are committed to creating an inclusive workplace. We invite all qualified individuals to apply. Robertson & the clients we represent are equal opportunity employers, committed to diversity and inclusion. Robertson is a certified diverse supplier and actively seeks to foster a representative and inclusive workforce. We welcome applications from all qualified individuals, regardless of race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, protected veteran status, Aboriginal status, or any other legally protected factors. We champion building a diverse and inclusive environment.