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In office (Chennai)
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Ford is an American automaker founded in Dearborn in 1903 by Henry Ford, who introduced the moving assembly line and turned the car into a mass-market product. It is now organised into three businesses reported separately: Ford Blue for internal combustion vehicles, Model e for electric vehicles and software, and Ford Pro for commercial customers, which bundles vans and trucks with telematics, servicing and charging under multi-year contracts. Listed on the New York Stock Exchange and still partly controlled by the founding family through a special class of shares, its F-Series pickup has been the best selling vehicle in the United States for decades.
  • Develop and validate credit risk models

  • Enhance the usage of Artificial Intelligence / ML and transform into more efficient solutions.

  • Using GCP, SAS, R, Python, for model building and model validation

  • Continual enhancement of statistical techniques and their applications in solving business objectives

  • Compile and analyze the results from modeling output and translate into actionable insights

  • Prepare PowerPoint presentations and document preparation for the entire credit risk modeling process

  • Collaborate, Support, Advise and Guide in development of the models

  • Acquire and share deep knowledge of data utilized by the team and its business partners

  • Participate in global conference calls and meetings as needed and manage multiple customer interfaces

  • Execute analytics special studies and ad hoc analyses

  • Evaluate new tools and technologies to improve analytical processes

  • Set own priorities and timelines to accomplish projects (accountability for project deliverables)

  • Masters in Finance, Financial Engineering, Analytics or Mathematics, Computer Science, Statistics, Industrial Engineering, Operations research, or related field.

  • Good understanding of Probability of Default (PD), LGD and EAD modeling technique.

  • Proven hand-on experience in Artificial Intelligence and extensive experience in GCP .

  • Very good understanding of Predictive modeling techniques and their application.

  • Knowledge of Credit life cycle

  • Statistics and machine learning techniques.

  • Conducted and applied statistical methodologies including linear regression, logistic regression, ANOVA/ANCOVA, CHAID/CART, cluster analysis

  • Team player and collaboration skills.

  • Programming skills in GCP, R, SAS, and PYTHON.

  • Fluency with Excel, PowerPoint and Word

  • Strong written and oral presentation / communication skills - must have the ability to convey complex information simply and clearly

  • Experience with developing and implementing cloud based analytical solutions in GCP or similar set up.

  • Masters in Mathematics/Statistics/Economics/Engineering or any other related discipline or a track record of performance that demonstrate this ability

  • Practical applications of mathematical modeling and Artificial Intelligence

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