Job Purpose and responsibilities:
• Tackle the most challenging puzzles in the Financial Fraud Detection domain leveraging advanced Analytics and Machine Learning algorithms.
• Conduct large-scale data analysis and develop predictive models for the largest Financial institutions in the world.
• Develop, define and share Modeling and Data Science practices.
• Communicate with Professional Services and with Clients regarding Machine Learning development plans, model performance and recommendations.
• Provide guidance for the design and development of proprietary Machine Learning tools, platforms and products.
• M.Sc in Computer Science, Statistics, Mathematics, Physics, Engineering or equivalent.
• Minimum of 3 years experience with statistical model development. Deep and diverse experience with multiple statistical procedures and data mining algorithms, including Classification, Regression and Clustering.
• Experience in modeling with Python and/or R.
• Vast experience using SQL.
• Strong analytical skills and agility with using quantitative tools to solve analytical problems.
• Good oral and written communications skills, and ability to interact with software developers, project managers, business analysts, product managers and with clients.
• Ability to work in multi-disciplinary agile teams.
• Innovative aptitude.
Additional Desired Qualifications:
• Experience in Unsupervised and Anomaly Detection methods.
• Knowledge of Financial systems and\or Fraud Detection.
• Experience with Big Data technologies such as Spark, Cassandra, Hadoop, Map-Reduce processes etc.
• Leadership skills.