Data Scientist II – Model Validation and Monitoring

Vytwo Technologies Inc.; Prosper (TX); On-site; USD 90,000 - 120,000; Full time

Job summary

Vytwo Technologies Inc. is seeking a Data Scientist II focused on model validation and monitoring, responsible for delivering machine learning models and ensuring their performance. This role will lead model monitoring, validate model performance, and aggregate data to address anomalies.

The ideal candidate will have at least 2 years of experience in data science, proficiency in Python and SQL, and familiarity with Spark. Applicants should be able to explain complex results to non-technical audiences, making clear communication essential.

Qualifications

• 2 years of experience in data science, engineering, or mathematics.
• Experience in developing data science pipelines in Python or R.
• Ability to handle terabyte size datasets using Spark.

Responsibilities

• Lead model monitoring activities and track performance metrics.
• Conduct model validations including performance testing and benchmarking.
• Explore and aggregate data to uncover data anomalies.

Skills

Data Science

Machine Learning

Python

SQL

Data Visualization

Spark

Tools

Scikit-learn

PySpark

Job description

Role: Data Scientist II – Model Validation and Monitoring

Location: Scottsdale AZ (Onsite)

• US Citizen & GC Only
• Must be legally authorized to work in US without need for employer sponsorship now or at any time in the future.

Overall, Purpose

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 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

• A minimum of 2 years of data science, engineering, mathematics, or related work experience is required.
• 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.