Machine Learning Credit Model Developer

ING Hubs Poland is hiring!
 

The expected salary for this position: 9600 - 18 000 PLN gross.

The financial ranges specified in the announcement are adjusted and may differ from the range specified in the remuneration regulations.
 

We are looking for you, if you have:

• an advanced degree (PhD or Masters) in a quantitative discipline, such as Computer Science, Data Science, Statistics, Mathematics, Physics, Econometrics, Quantitative Finance or related field,

• excellent knowledge of classic machine learning methods: supervised and unsupervised learning, classification, regression, etc.;

• experience in validation or development of credit risk models in a financial institution or related industry,

• analytical skills with the ability to describe models, effectively articulate and document model’s structure, logic and results,

• experience writing code in Python (R, SAS or other statistical programming language as a plus), data processing and advanced visualization,

• knowledge of credit risk management process, including application of credit risk models like e.g., credit decision scorecards, early warning systems, collection systems, IRB, IFRS9 etc.

• english verbal and writing proficiency.

You'll get extra points for:

• knowledge of regulatory framework for credit risk management (IRB, IFRS9, etc.) and lending process,

• experience with the Agile way of working,

• code versioning - git.
   

Your responsibilities:

• perform development and periodical monitoring of credit decision models across global ING business lines and locations,

• ensure models are conceptually sound and appropriate,

• ensure model compliance with regulations, internal policies and industry best practices,

• collaborate closely with cross-functional teams including model validator, risk managers, and business stakeholders and promote best practices,

• stay up-to-date with industry trends and regulatory guidelines, in particular related to advanced analytics models to be able to contribute to the continuous improvement of credit decision models.

Information about the Team:

Who are we?

• we are a fast growing, international team of experts developing non-regulatory credit risk models. As a part of a Risk Hub Model Development Area we focus on applying machine learning techniques to ensure credit-risk decision making is safe and reasonable to provide a relevant support for business growth.

What is our mission?

• we are responsible for developing and monitoring advanced analytics non-regulatory models used by ING,

• on a daily basis, we have frequent collaborations with our colleagues in ING around the world, and provide them with relevant and timely expertise in credit risk models and driving their lending business,

• our goal is to ensure sustainable credit risk model performance. We strive to bring fresh ideas to life and embrace challenges in a fast changing and complex environments.

How can You grow with us?

• gain a great visibility across global ING business lines and locations; explore a possibility to grow in your expertise, with a lot of opportunities to share knowledge (internally and externally),

• broaden programming skills in Python or other statistical tools/stack in developing machine learning solutions,

• expand the hands-on skills in developing credit risk decision models (acceptance models, behavioral models, EWS, etc.) for individual and business clients,

• deep dive into models during periodical monitoring of  credit risk decision models performance (acceptance models, behavioral models, EWS, etc.) for individual and business clients,

• learn the best practices in ensuring model compliance with regulations, internal policies and industry best practices,

• develop collaborative skills in dealing closely with cross-functional teams including model validators, risk managers, and business stakeholders,

• stay up-to-date with industry trends and regulatory guidelines, in particular related to machine learning and advanced analytics models to be able to contribute to the continuous improvement of credit risk models.

How do we work?

• by bringing in our technical and business expertise we assure that models are appropriate for intended use, compliant with