Data Science Specialist

Responsibilities

1. Contribute to the design and implementation of Population, Gender, and Diversity Statistics policies and procedures covering all areas of activity.
2. Supervise day-to-day activities to ensure compliance with stipulated policies and procedures.
3. Identify opportunities for continuous improvement of systems and processes taking into account leading practices, changes in business environment, cost reduction and productivity improvement.
4. Establish working relationships with relevant internal and external stakeholders.
5. Collect feedback from internal and external stakeholders on issues being faced and other requirements.
6. Contribute to the preparation of progress reports directed to all relevant stakeholders to keep them informed of progress.
7. Actively gain exposure and insights to local market development, business opportunities and the existing regulatory landscape.
8. Actively participate in on-the-job training, mentoring, and coaching of subordinates.
9. Provide clear direction, prioritize tasks, assign and delegate responsibility and monitor the workflow.
10. Promote a high-performance working environment embracing the company's values.
11. Develop guidelines and plans for data analysis leveraging latest industry updates, best practices, and market trends.
12. Conduct detailed feasibility assessments and develop briefs and business cases for new data analysis initiatives (i.e., new data sources, innovative data analysis methods, etc.) and projects.
13. Develop technical proposals for data analysis initiatives and projects including detailed description of the proposed work and resources required.
14. Engage with concerned stakeholders to identify business requirements and expectations, define project scope, request clarifications as needed, and communicate to relevant stakeholders.
15. Translate business needs into problem statements while leveraging internal and external sources.
16. Develop implementation plans for data analysis projects and initiatives highlighting key milestones, methods and resources required.
17. Follow up on data gathering activities to ensure data accuracy and completeness in a timely manner and according to pre-defined guidelines and plans.
18. Ideate technical platforms and algorithmic engines, and support in coding scientific models and algorithms.
19. Review and evaluate model lifecycle including data cleansing, model development and validation, and model deployment.
20. Assess and support in conducting periodic tests and validation checks for deployed algorithms and models.
21. Review data analysis to evaluate integrity and validity of outcomes and methods used, and ensure alignment with requirements and targeted outcomes.
22. Facilitate and manage the coordination between internal and external experts throughout the data analysis lifecycle to ensure alignment on requirements and expectations, and identify and escalate unresolved issues.
23. Gather consolidated data analysis reports to assess insights and review methodologies used to ensure validation of outcomes and adherence to data analysis standards and guidelines.
24. Engage with concerned internal / external stakeholders and conduct presentations to share analyses outcomes and findings.
25. Track KPIs and analyze feedback collected from concerned stakeholders to develop periodical reports reflecting the performance of data analysis projects / initiatives.

Qualifications

1. 6+ years of experience in a Data Science field.
2. Bachelor's Degree in Big Data and Analytics or equivalent is required.
3. Proficiency in Microsoft Office.
4. Proficiency in English.
5. Focuses on Results and Quality.
6. Demonstrates Customer Centricity.
7. Displays Integrity and Professionalism.
8. Innovates and Demonstrates Agility.

Desired Candidate Profile

Education: Bachelors in Computer Application (Computers)

Gender: nm

Nationality: Any Nationality