Avant is looking to leverage company data and third-party vendor data to drive business solutions and enhance customer experience through predictive modeling and data analysis.
Requirements
- 2+ years expertise in machine learning theories and practices (Generalized Linear Model, Support Vector Machine, Random Forest, Gradient Boosting, etc.)
- Familiarity with Object-Oriented Design (OOD) concept and functional programming with 2+ years experience writing production-level code
- Strong proficiency in Python with experience in the end-to-end development of machine learning models
- Advanced in SQL for querying and analyzing large datasets
- Experience with ML and data analytics platforms/technologies such as Databricks, AWS (including AI/ML tools) and Looker is a plus
- Experience in deep learning is preferred
- Experience in a data science or ML Ops role at a banking/financial institution or fin-tech is a plus
Responsibilities
- Design and build predictive models to enhance customer experience, reduce risk, improve revenue generation, optimize direct mail targeting, and drive key outcomes throughout the customer lifecycle
- Mine and analyze data from company databases to drive optimization and improvement of product development, marketing techniques and business strategies
- Clean, process and validate data to ensure its quality and integrity for modeling and analysis
- Conduct feature engineering, select appropriate features and develop robust models using various machine learning techniques
- Perform ad-hoc analysis and present results in a clear manner to senior management
- Develop and enhance processes and tools to monitor model performance and input and output data accuracy
- Proactively collaborate with Data Engineering, ML Operations, Software Development, Credit Risk, Marketing, Legal & Compliance, and other internal groups to implement and monitor models across the customer lifecycle
Other
- 2-3 years of the job experience as a data scientist or an advanced degree (Master’s or PhD in Machine Learning, Computer Science, Statistics, Operations Research or a related STEM fields)
- Excellent communication skills, with the ability to present complex concepts and findings clearly to both technical and non-technical audiences, and effectively collaborate with cross-functional teams
- Strong problem-solving and critical-thinking skills, with a keen attention to detail and data integrity
- Hybrid schedule (M, T, Th in-office) enables flexibility to balance work and individual priorities
