Title: Data Scientist
POSITION TITLE: Mortgage Risk Modeling Data Scientist
Company Overview:
At Codvo, software and people transformations go hand-in-hand. We are a global empathy-led technology services company. Product innovation and mature software engineering are part of our core DNA. Respect, Fairness, Growth, Agility, and Inclusiveness are the core values that we aspire to live by each day.
We continue to expand our digital strategy, design, architecture, and product management capabilities to offer expertise, outside-the-box thinking, and measurable results.
The Deployment Specialist ensures a smooth customer experience across all interactions.
JOB SPECIFICATIONS
Position Overview
Develop a cutting-edge mortgage risk model to assess and measure default risk, directly impacting outbound customer contact strategies. This role involves deep-diving into mortgage data to build predictive models that inform critical business decisions.
Essential Duties And Responsibilities
- Leverage strong understanding of regulatory requirements in the mortgage industry, ensuring model compliance.
- Utilize advanced data analysis skills to understand data related to mortgage servicing, payment histories, borrower information, and economic indicators.
- Apply knowledge of various credit and financial risk assessment methodologies to design and implement a robust risk scoring system.
- Proactively identify and address challenges related to data quality and model performance, ensuring accuracy and reliability.
- Effectively collaborate with the omnichannel team to gather requirements, understand data needs, and translate them into actionable model inputs.
- Develop and optimize queries in SQL, Snowflake, Scala, Ruby, Python, or similar languages for building and refining the risk score model.
- Demonstrate expertise in data governance principles and practices, maintaining data integrity throughout the modeling process.
Qualifications and Experience [4 to 7 years]
- Proven experience in developing and implementing mortgage risk models within a financial services environment.
- Strong understanding of statistical modeling techniques, including regression analysis, machine learning, and time series analysis.
- Proficiency in SQL, Snowflake, or similar query languages for data extraction and manipulation.
- Experience with statistical programming languages such as Python (with libraries like pandas, scikit-learn) or R.
- Strong analytical and problem-solving skills, with the ability to draw insights from complex data sets.
- Excellent communication skills, with the ability to convey technical information to both technical and non-technical audiences.
