Kıdemli Veri Bilimcisi/Makine Öğrenimi Mühendisi

01  Responsibilities

  • Apply machine learning and statistics expertise to solve analytical problems mainly in finance and location analytics.
  • Work closely with a software development team to convert analytic results into software products.
  • Use machine learning expertise to conceptualize new solutions for financial or other problems.
  • Communicate and document progress and results to the customers and produce analytical reports.

02  Requirements

  • BS or preferable MS degree in Computer Science, Computational Science, Data Science or general Engineering or related disciplines from a reputable university.
  • Solid theoretical understanding of machine learning concepts and algorithms.
  • Practical experience with supervised and unsupervised machine learning algorithms (e.g. random forest, multilayer perceptron, SVM, k-means clustering, PCA).
  • Experience with Python 3 and its scientific computation and visualisation packages (e.g. numpy, pandas, scikit-learn, matplotlib).
  • Skills in data preprocessing, cleaning and data visualisation.
  • Proficiency (theoretical know-how) in probability and statistics.
  • Good working experience with SQL is necessary to extract and work with data residing in RDMSes.
  • Fluency in written/spoken presentation of analytical results in English.

03  Nice to Haves

  • Experience with deep learning libraries is a plus (e.g. TensorFlow, PyTorch).
  • Experience with an additional, OOP language is a plus (e.g. C#, C++).
  • Experience with distributed big-data computing frameworks is a plus (e.g. Hadoop, Spark, Kafka).
  • Experience with financial data and solutions experience is a plus.
  • Experience with Time-Series Forecasting is a big plus.
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