Associate, Data Science, Credit Risk
$95k - $130kAvant
Avant is adding to our Data Science team! We are looking for a self-driven candidate who is passionate about problem solving and interested in making a difference. This person will be a key member of our Data Science team and responsible for the development of numerous kinds of customer lifecycle models. If you are looking for an opportunity to join a great team where you can be yourself, deepen your skills and experiences, and find new areas of inspiration then consider a career at Avant!
What you'll do at Avant:- Work with stakeholders throughout the company to identify opportunities for leveraging company data and third-party vendor data to drive business solutions using different modeling techniques
- 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
- Design and build robust credit risk models, including application scorecards, behavioral models, loss forecasting, and risk-based pricing, to optimize underwriting decisions and drive overall portfolio performance.
- 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. Provide timely and justified recommendations in response to ad-hoc analysis requested by internal groups
- 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
- Develop and enhance processes and tools to monitor model performance and input and output data accuracy
- Master's or PhD degree in Machine Learning, Computer Science, Statistics, Operations Research or a related STEM fields
- 2-3 years of professional experience in machine learning or data science within the consumer credit/lending or fintech industry
- Strong expertise in machine learning theories and practices (Generalized Linear Model, Support Vector Machine, Random Forest, Gradient Boosting, Deep Learning, etc.)
- Familiarity with Object-Oriented Design (OOD) concept and functional programming with 2+ years experience writing production-level code
- Proficiency in Python with experience in the end-to-end development of machine learning models. Strong domain expertise and technical knowledge of credit risk modeling
- Advanced in SQL for querying and analyzing large datasets
- 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 analytical, problem-solving and critical-thinking skills, with a keen attention to detail and data integrity
- Preferred: Experience with ML and data analytics platforms/technologies such as Databricks, AWS (including AI/ML tools) and Looker
[If an outstanding applicant's experience and skill level is above or below the qualifications outlined in the job posting, we reserve the right to make an offer at a different level than the one listed in this job posting, which may have a different compensation range.] This role is eligible for additional incentives, including an annual bonus. These rewards are allocated based on level, impact and performance in the role. Our benefits include:
- Choice of great Medical, Dental, and Vision Insurance Plan options
- 401(k) match
- Flexible Time Off
- Flexible Work Environment - (i.e. Mon/Tues/Thurs in-person)
- Generous Paid Parental Leave, Adoption Assistance and Post-parental leave ramp-up program
- Lunch Allowance (Fooda) and In-office Snacks
- Summer Fridays
- Fun In-Office and Virtual Social Events
- And who doesn't love the swag
$111.2k - $126.9k
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