What are the responsibilities and job description for the Data Scientist position at iBusiness Funding?
About Us:
iBusiness Funding is a technology company focused on our mission to provide working capital to small and medium-sized businesses in an efficient and transparent manner. We are a leader in providing innovative lending solutions for banks and financial institutes, with a specialization in SBA lending. We build scalable lending platforms that streamline the business lending process, allowing lenders to efficiently deliver capital to small and medium-sized businesses.
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. In this role, you will:
- Develop and maintain credit risk models and tools to evaluate the creditworthiness of small business loan applicants.
- 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.
Education and Experience:
- 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.
- 2 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.
Physical Demands:
The physical demands of the position are typical of those found in a traditional office environment. Employees will not need to walk significant distances nor lift substantial weight. Employee will need to be able to remain seated at a desk for 8-9 hours in a typical workday.
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.
