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FC

Senior Data Scientist (Credit Risk Modelling)

FCC / FAC
FCC Tower Floor 10, United Statesfull_timeVerifiedPosted 23 Jul 2024
💰 $139,803/yr($103,331/yr$139,803/yr)

About the role

Closing Date (MM/DD/YYYY):

08/02/2024

Worker Type:

Permanent

Language(s) Required:

English

Term Duration (in months):

Salary Range (plus eligible to receive a performance based incentive, applicable to position) :

$103,331 - $139,803

Risk management expertise needed
Use your advanced knowledge of model development – including expertise in credit risk adjudication and risk measurement practices for allowance for credit loss, capital management and stress-testing – to support risk management at FCC.
This role requires expert working knowledge of structured and unstructured data, statistical programming languages and mathematical concepts.

What you’ll do:

  • Lead complex insights projects to find patterns and trends in data, and model or project future scenarios

  • Determine technical direction in data solutioning, including methodology and tools used

  • Unlock insights from complex and diverse groupings of internal and external data, and tell a story with the data that enables enlightened decision-making

What we’re looking for:

  • Analytical thinker who can solve complex data problems and find ways to improve FCC through data

  • Confident communicator able to translate knowledge for others

  • Master of one or more predictive and descriptive analytics tools and techniques

  • Organized multi-tasker with demonstrated expertise using tools to manipulate and prepare huge sets of data for analysis

What you’ll need:

  • A master’s degree in one of the noted domains and at least six years of experience (or an equivalent combination of education and experience)

  • Expert level understanding of the specified domain

  • Strong mathematical or statistical background

  • Mastery in visualization and analytics tools including, but not limited to, SAS, MS Power BI, AWS environment and tools, R, Python.

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Company

FCC / FAC

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