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The successful Data Scientist will be responsible for developing cutting edge credit risk models over big data. He/she will work closely with the Big Data and Analytics Director and the rest of the team to develop advanced credit-risk models and algorithms for nano- and micro-finance.

Working closely with other creative minds, the candidate will be able to demonstrate his/her expertise on data, models and machine learning, as well as his/her high level of analytical and creative skills. He/she will have the opportunity to further develop knowledge and expertise on AI, machine learning, predictive and risk analytics.

Responsibilities

  • Design and implement credit risk models and algorithms beyond the state of the art.
  • Develop and deploy advanced profit scoring models.
  • Identify credit risk factors by applying computational methods to large data volumes.
  • Apply deep and ensemble learning to optimize risk models.
  • Determine optimal risk strategies through computational means.
  • Deliver credit-risk insights through big data risk analytics.

Qualifications & Skills

  • BSc and MSc in Mathematical Sciences or Computer Science from an accredited institution.
  • Hands-on experience at least in two of the following (with descending significance):
    • Machine learning and AI
    • Credit risk models
    • Big-Data; Apache SPARK
    • Risk Analytics
    • Predictive Analytics
    • Mathematical & Statistical modelling
  • Ability to efficiently search and understand the scientific literature of mathematical models, machine learning and AI.
  • Ability to judge the relevance of existing models and algorithms to specific business needs.
  • Strong analytical skills.
  • Excellent judgment and problem-solving skills.
  • Passion for learning, exploring and developing new models and machine learning and AI algorithms.
  • Ability to hit tight deadlines and work under pressure and strict attention to detail.

Will be considered a plus.

  • PhD in Computer Science, Mathematical Sciences or Finance from an accredited institution.
  • Hands-on experience of big data processing and analytics.
  • Hands-on experience of data bases (SQL and NoSQL).
  • Communication skills.
  • Creative skills.
  • Programming skills.
  • Hands-on experience of Java.

Εταιρεία: ChannelVas

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