https://bayt.page.link/8J6JasWCvm9wih2v7
أنشئ تنبيهًا وظيفيًا للوظائف المشابهة

الوصف الوظيفي

Job Role:
The core of Quant is Data Science, and hence it requires highly capable individuals that can deliver the level of quality our clients have grown accustomed to, and to have a mindset that’s highly agile, critical and curious. The Data Scientist is required to collect, analyze and interpret large data sets in order to develop data-driven solutions, insights, and visualizations for difficult business challenges.

Job Responsibilities:
  • Collaborate with key stakeholders to understand their needs and challenges through their data in order to devise potential solutions.
  • Mine and analyze data from stakeholders’ databases in alignment with their requirements to conclude optimization recommendations.
  • Research and develop statistical learning models for data analysis.
  • Implement new statistical or other mathematical methodologies as needed for specific models or analysis.
  • Optimize joint development efforts through appropriate database use and project design.
  • Enhancing data collection procedures to include information that is relevant for building analytic systems.
  • Creating automated anomaly detection systems and constant tracking of its performance.
  • Documenting reports and developing presentations that include the project deliverables, findings and recommendations with key decision makers.
  • Extending company’s data with third party sources of information when needed.
  • Staying up-to-date with the latest technology trends.

RequirementsAcademic Prerequisites:

Bachelors and/or Master’s degree in Statistics, Mathematics or another quantitative field and/or Computer Science.

Skills Required:
  • Proficiency in python.
  • Proficiency in data science frameworks such as scikit-learn, ts-learn, scipy, tensorflow, pytorch, etc
  • Has sensible statistical knowledge.
  • Experience in data visualization.
  • Experience in analytics
  • Good grasp of data engineering concepts and tools.
Skills Required:

  • Experience in geospatial data and analytics.
  • Experience and time series analytics.
  • Experience in unsupervised machine learning.
  • Experience in transactional databases.
  • Experience in modelling.
  • Experience in data engineering tasks.


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