Data Scientist II – Model Validation and Monitoring
Role summary
This contract role in Scottsdale, AZ, is for a Data Scientist II focused on Model Validation and Monitoring. The position involves providing critical challenges to model development, conducting ongoing model monitoring, performing root cause analysis for performance issues, and exploring/validating/deploying machine learning models. Key responsibilities include tracking performance metrics, detecting drift, identifying data quality issues, and recommending remediation. The role requires strong Python, R, SQL, and Spark skills for handling large datasets and writing production-level code, along with experience in various ML techniques and data visualization. Collaboration with Product and Engineering teams and clear communication to non-technical audiences are essential.
Hi,
Our client is looking for a
Senior Data Scientist
with a contract project in
Scottsdale, AZ
below is the detailed requirement.
Job positing Title : Data Scientist II – Model Validation and Monitoring
Location: Scottsdale AZ
Type: Contract
Job description:
This position serves as a data science team member in the Model Validation and Monitoring Team delivering leading edge machine learning models to our clients. This includes providing effective challenges to model development, conduct model monitoring and performance tracking, provide root cause analysis of model performance, exploring, building, validating, and deploying models.
Essential Functions
:
• Lead model monitoring activities, including tracking performance metrics, detecting model and data drift, identifying data quality issues, providing root cause analysis, and recommending remediation strategies.
• Conduct rigorous model validation by providing effective challenges during model development phases, including performance testing, benchmarking, provide remediation plan, and documentation to ensure models meet business, technical, and regulatory standards.
• Explore and aggregate data independently to uncover data anomalies that impact algorithm performance
• Write production level code in a dynamic, start-up environment
• Solve complex problems using terabyte size data sets
• Apply of a variety of machine learning techniques to a business problem to arrive at optimal approach
• Partner with Product and Engineering teams to solve problems and identify trends and opportunities
• Explain and visualize results and algorithm performance to non-technical audiences
Minimum Qualifications
• Experience developing data science pipelines & workflows in Python, R or equivalent programming language. Experience in writing and tuning SQL. Experience handling terabyte size datasets with Spark language.
• Experience applying various machine learning techniques, and understanding the key parameters that affect model performance
• Experience using ML libraries, such as scikit-learn, mllib, etc.
• Experience using data visualization tools
• Able to write production level code, which is well-written and explainable
• Ability to effectively communicate findings from complex analyses to non-technical audiences.
Preferred Qualifications
• Experience of using advanced ML algorithms building, testing, and deploying fraud models.
• Hands-on experience with PySpark
• Industry experience in building or validating machine learning models
• Experience exploring data and finding hidden patterns and data anomalies
