Advanced Analytics Consultant

Job purpose:

Understand Business requirements; implement proper data models; data migration and data presentation solutions. Interpret data; analyze results using statistical techniques; besides being the company's internal consultant in all BI and AA matters across all projects and an external consultant to customers on data management matters.

Key accountabilities and decision ownership:

• Collect and gather data from different sources through different methods
• Identify and understand the collected data then transform it to the desired format
• Support testing and fix bugs on a timely manner
• Implement requirements and design through the development of data pipelines
• Transfer knowledge to the support team by supporting post production bugs fixing
• Design the solution and create data models
• Perform data analysis for the purpose of identifying data quality issues and data mapping
• Contribute with the commercial team with designing and authoring the technical proposal in terms of the architecture; in scope; out of scope; assumptions; and dependencies.
• Build POCs (proof of concept)
• Ensure best practices for security are being applied
• Manage DataOps by establishing the pipeline needed to manage the data artifacts and MLOPs by conducting ML experiments and roll the best model to production
• Contribute proactively to customer solutions and formulate customer offerings including new business lines and potential selling points
• Develop predictive models that satisfy the business needs
• Coach; mentor; and support junior and senior members of the team from a technical perspective

Must have professional qualifications:

• 12+years of data management and advanced analytics experience
• Bachelor's degree of computer science or relevant
• Masters in computer science OR equivalent academic studies in Machine Learning and Statistics
• Professional in Microsoft SSIS
• Professional in R or Python
• Experience in SQL and data modelling is a must
• High pattern recognition ability: ability to find generic patterns that handle as many cases as possible with fewer lines of code.
• Experience in data architecture; data engineering; data visualization; DataOps; and databases is a must (specific technologies based on projects/hiring needs)