Data Scientist

  • Anywhere

Job Description

  • Conduct day-to-day activities while ensuring compliance to policies and procedures
  • Contribute to the identification of opportunities for continuous improvement of systems, processes in line with leading practices
  • Establish working relationships with relevant internal stakeholders
  • Collect feedback from internal stakeholders on issues being faced and other requirements
  • Contribute to the preparation of progress reports directed to all relevant stakeholders to keep them informed of progress
  • Support in the identification of the latest updates in data science and artificial intelligence fields for continuous improvement and innovation at 
  • Support in feasibility studies and business cases development for relevant data analysis initiatives and projects
  • Support in developing technical proposals for data analysis initiatives / projects including detailed description of the proposed work and resources required
  • Participate in workshops with concerned stakeholders to identify business needs, project scope and problem statement, and request clarifications as needed i
  • Identify and secure needed data from relevant sources and establish interfaces when needed to facilitate complex data extraction
  • Request data access permissions as needed and follow up on unavailable / incomplete data sets to ensure data readiness in a timely manner and according to pre-defined plans
  • Design standardized and customized reporting dashboards and databases based on the relevant data pipelines and identified requirements
  • Build complex data sets from multiple sources through data cleansing and integration into dashboards to facilitate downstream data activities 
  • Perform complex data mining, utilize APIs and build ETL pipelines to identify trends and patterns in large data sets
  • Develop and test models and machine learning algorithms based on in-depth understanding of underlying data, data structures, and business needs
  • Apply machine learning techniques to the data to identify the model that best fits requirements and expectations, and tune the model accordingly
  • Monitor deployed models through conducting periodic tests and validation checks
  • Conduct exploratory and predictive data analyzes to highlight hidden correlations and insights leveraging predictive modeling 
  • Conduct technical hypothesis testing on all outcomes to ensure extracted insights are accurate and in line with requirements and expectations
  • Review and consolidate all data analysis and analytics reports, and prepare presentations to communicate complex quantitative analyzes leveraging data visualization
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