Data Scientist in Financial Markets

Gefunden in: beBee S CH - vor 1 Monat

Zürich, Schweiz Swisslinx Vollzeit
As one of the premier supplier to our client, one of the most established financial institutions in Switzerland, Swisslinx are looking for a Data Scientist.
Job Description:
  • Build data infrastructure for Trading Analytics, including Databases and Data Lake.
  • Develop Machine Learning and Financial models for Trading Execution, Market Making, and Sales.
  • Ensure data quality, including mining, cleansing, and analyzing large datasets for use-case development.
  • Write well-documented production code and algorithms, mainly in Python and Scala.
  • Create software applications, user interfaces, APIs, dashboards, and automated reports for business users.
  • Build systems for collection and transformation of large data sets to enable model development.
  • Understand Machine Learning literature and techniques to mentor team members.
  • Assist with the execution of Big Data solutions and related technologies.
  • Present results from AI and Financial models to stakeholders.
  • Collaborate with Data Architects, Developers, and Business Developers to jointly meet deadlines.
Required Skills:
  • Master or PhD in a technical field, such as Mathematics, Physics, Engineering, Computer Science, or alike.
  • 4+ years of work experience as a Data Scientist.
  • Proven knowledge of Machine Learning and Artificial Intelligence, including Advanced Statistical Analysis, Data Mining, Bayesian Statistics, Reinforcement Learning, and Deep Learning.
  • Advanced coding skills in programming languages such as Python, R, Matlab, Scala, C++, and/or Java.
  • Knowledge of Webapp Development, Docker, Kubernetes, Git, and Dash (or similar).
  • Knowledge of Data Architecture, Databases (including Oracle, MSSQL, and MongoDB), Data Lakes, and Cloud Computing (e.g. MS Azure or Snowflake).
  • Knowledge of PowerBI, Tableau, and VBA.
  • Knowledge of Mathematical Finance and Financial Markets, including Algorithmic Trading, Financial Derivatives, Portfolio Management, and Dynamic Optimization methods.
  • Knowledge of Spark, Databricks, Kafka, and real-time analytics is a plus.
  • Collaborative, team player, open-minded, and easy to work with.
  • Proficient presentation skills and high attention to detail.
  • Able to explain technical results to non-technical audiences.
Do you think this could be an ideal position for you? If you are interested in this challenge, then please send your full CV to the link on this page. We look forward to hearing from you.

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