About iBusiness Funding
iBusiness Funding is a software and lender service provider specializing in small business lending. Our technology, team, and process enable us to support loans from $10,000 to $25 million for our lending partners. Our technology solutions have been proven to quickly scale our clients’ portfolios without the need for additional overhead. Our flagship product, LenderAI, features end-to-end lending functionality from sales all the way through servicing
To date, we’ve processed over $11 billion in SBA and non-SBA volume and handle more than 1,000 business loan applications daily. Our team is driven by our core values of innovation, integrity, enjoyment, and family.
Join us and be part of a team that’s transforming the finance industry and empowering businesses to thrive!
Role Description:
We are looking for a Data Scientist join our Decision Sciences team and contribute to the development of credit risk decisioning tools for small and medium sized businesses.
Major Areas of Responsibility:
In this role, you will:
- Develop and maintain credit risk models and tools to evaluate the creditworthiness of small business loan applicants.
- Apply machine learning model development techniques, including XGBoost, Gradient Boosting, Random Forest, and Logistic Regression, with responsibility for feature engineering, hyperparameter tuning, cross-validation, model evaluation, and interpretability.
- Collect data from various structured and unstructured sources, producing creative new features for use in models.
- Carefully monitor model performance and advise on Model Risk Management strategy.
- Produce detailed model documentation for stakeholders and regulators.
- Work with product teams to deploy models to a cloud environment.
- Interact with various stakeholders, providing expert guidance on how best to utilize machine learning to achieve business objectives.
- Work with the credit strategy and customer analytics teams to get the most value out of the models built.
- Support ad-hoc risk analyses and projects as required.
Required Knowledge, Skills, and Abilities:
- Machine learning model development experience (e.g., XGBoost, Gradient Boosting, Random Forests, Logistic Regression) including feature engineering, hyperparameter tuning, cross-validation, model evaluation, and interpretability techniques
- Strong analytical background with data-driven decisioning mindset.
- A bachelor’s degree in mathematics, statistics, finance or a related field. A master's degree or professional certification (e.g., CFA, FRM) are a plus.
- 5+ years of experience in risk management, data analysis, or a similar role with a focus on deploying production credit risk models, particularly within the financial services or lending industry.
- 3+ years of Python experience, specializing in data science and machine learning, with proficiency in libraries such as Pandas, Numpy, and SKLearn.
- Proven experienced in collecting and cleaning data from diverse sources using common MLOps tools such as Git, Docker, and AWS
- A collaborative team player with a strong ability to work effectively in remote environments.
- Excellent communication skills, especially as it relates to explaining key concepts to a non-technical audience.
- Skilled in engaging with multiple stakeholders and managing several projects simultaneously.
Conclusion:
This job description is intended to convey information essential to understanding the scope of the job and the general nature and level of work performed by job holders within this job. This job description is not intended to be an exhaustive list of qualifications, skills, efforts, duties, responsibilities, or working conditions associated with the position.
The company is an equal opportunity employer and will consider all applications without regard to race, sex, age, color, religion, national origin, veteran status, disability, genetic information, or any other characteristic protected by law.