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Cecl Python Jobs in Virginia (NOW HIRING)

Capital One

Principal Quantitative Modeler

Mclean, VA · On-site

$55.25 - $71.75/hr

... CECL/allowance, stress testing, and capital allocation for Capital One. Our models and analyses ... Programming in R, Python or SQL * Presenting statistical concepts and research results to non ...

Capital One

Principal Quantitative Modeler

Mclean, VA · On-site

$55.25 - $71.75/hr

... CECL/allowance, stress testing, and capital allocation for Capital One. Our models and analyses ... Programming in R, Python or SQL * Presenting statistical concepts and research results to non ...

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Cecl Python information

What is the difference between Cecl Python vs Cecl Data Analyst?

AspectCecl PythonCecl Data Analyst
Required CredentialsPython programming skills, financial modeling knowledgeData analysis skills, SQL, Excel, possibly some programming
Work EnvironmentDeveloping models, coding, testing in financial institutionsData interpretation, reporting, supporting decision-making
Industry UsageUsed by quantitative teams, risk management, model developmentUsed by business analysts, risk teams, finance departments

Cecl Python focuses on developing and implementing CECL models using Python programming, while Cecl Data Analysts primarily interpret data, prepare reports, and support model validation. Both roles are essential in financial institutions but differ in technical depth and daily tasks.

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Data Science - Advisor / SME

Reston, VA • On-site

Technology Ventures
IT Services • 51 - 200 employees
Learn more about Technology Venturesexternal

Other

Posted 6 days ago

Job description

Job Title : Data Science - Advisor / SME
Location : 3 days onsite / week 1100 15th Street Northwest VA USA 20190 Duration : 6 Months Contract to start
Description:
  • The Finance - Data Science - Advisor role will offer you the flexibility to make each day your own, while working alongside people who care so that you can deliver on the following responsibilities:
  • Use advanced mathematical, analytical, or econometric tools to create algorithms and analyses that will be used to support the Multifamily CECL and DFAST/forecasting processes within the Finance organization.
  • Research and evaluate model results and perform credit-related analyses for both expected and stress scenarios including CECL/DFAST.
  • Coordinate team activities with product and/or business owners, data engineers, and platform teams to understand business needs and current capabilities, data availability, and alternative uses to drive success of parts of projects, programs, or products.
  • Ensure application of statistical modeling capabilities from disciplines, such as computer science, computational science and methods, statistics, econometrics, data optimization, and data visualization.
  • Build predictive analytic capabilities within the team to enhance the delivery of business applications, and support the integration of data and statistical models or algorithms.
  • Apply innovative industry practices in research and testing to product development, deployment, and maintenance.
  • Oversee the design and build of new modeling applications to support risk measurement, financial valuation, decision making, and business performance for parts of products or initiatives.
  • Ensure the team communicates complex ideas and solutions effectively to business partners through data visualizations, technical documentation, and non-technical presentation materials.
Minimum Required Experiences
Total 10 years and 6 years in Data Science
Desired Experiences
Bachelor degree or equivalent
A Master's degree or equivalent in Data Science, Applied Economics, Statistics, or other similar graduate studies
  • Familiarity with advanced techniques including machine learning and natural language processing (NLP)
  • Prior quantitative and finance training, including forecasting/stress testing (DFAST) knowledge.
  • Ability to direct and evaluate the more technical aspects of data analysis and research, while also managing team in a timely manner to focus on the broader context and key impacts of the analysis
  • Ability to build and maintain strong business relationships with partners
  • Strong written and verbal communication skills
  • Relationship management including managing and engaging stakeholders, partners, customers, and building relationship networks
  • Strong analytical and problem-solving skills to conduct and manage analysis to address complex business problems
  • Programming including coding, debugging, and using relevant languages such as Python, R, SQL, or similar
  • Experience in the process of analyzing data to identify trends or relationships to generate business insights and inform conclusions about the data
  • Expertise in visualizing data to identify, summarize and explain observed data patterns

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