Risk Modelling Associate

Are you looking for an exciting opportunity to join a dynamic and growing team in a fast paced and challenging area? This is a unique opportunity for you to work in our team to partner with the Business to provide a comprehensive view.
 

As Risk modelling Associate, you will be responsible to review, test, document and perform other ad-hoc analysis with respect to vendor model solutions, with applications in risk management for its consumer and small business portfolio. You will help to steer long term profitable growth with strong business acumen, collaborate in a team environment, and effectively communicate results to senior management. If you are intellectually curious and have a passion for driving solutions across organizational boundaries, you may be the perfect fit for our team.

• Perform testing and document vendor models as per JP Morgan Chase Firmwide Governance guidelines
• Work closely with the senior management team to justify modeling solutions and help deliver them into production
• Collaborate with various partners in risk, technology, model governance, etc. throughout the entire modeling lifecycle (development, review, deployment, and use of the models)

Required qualifications, capabilities, and skills

• MS degree in Mathematics, Statistics, Computer Science, Operational Research, Econometrics, Physics, or other related quantitative one
• Minimum 3 years of experience in managing predictive risk models in financial industry
• Sense of ownership, ability to work on multiple projects in parallel 
• At least one year of experience and proficiency in coding (e.g., SAS, Python, Spark, or Scala) and big data technologies (e.g., Hadoop, Teradata, AWS cloud, Hive)

Preferred qualifications, capabilities, and skills

• Good understanding of advanced machine learning algorithms (e.g., regressions, XGBoost, Deep Neural Network – CNN and RNN, Clustering) will be added advantage
• Demonstrated expertise in data wrangling and model building on a distributed Spark computation environment (with stability, scalability and efficiency).