JOB DESCRIPTION:

Partner with various Lines of Business and their partners to deliver data-driven, actionable insights that inform and drive strategies and transformations for customers. This role intersects analytics, systems, and project delivery, providing thought leadership and innovation for analytical data. The primary responsibility is the extraction, transformation, and creation of analytically ready data for use in descriptive, diagnostic, predictive, and prescriptive analytics. This includes the effective and efficient build and management of data deliverables, encompassing design, development, documentation, support, and maintenance.

* PYTHON PROGRAMMING EXPERIENCE.

• Proficiency in working with data in multiple formats such as XML, CSV, flat files, SAS datasets, and Teradata database/server.

ABOUT US:

We are Delivery Centric, a dynamic technology company that is transforming the delivery of cloud implementations and Cyber security. We are headquartered in Australia with a global presence. We are tenacious, future-thinking, and highly driven to achieve an ambitious vision to be the leading global provider of innovative technologies for companies that keep our world clean, safe, and secure.
Our fast-paced and supportive environment will offer you lots of benefits, including a competitive salary, a friendly team, a healthy work environment, and opportunities for training and development

Why work with us?

• Work with diverse technologies, projects, clients and industries.
• Spend your days in a creative and innovative environment.
• Share experience and knowledge as part of an agile and dynamic team

APPLY NOW or share your resume to chrisabel.sherin@deliverycentric.com
Job Type: Full-time

Application Question(s):

• Please do mention your notice period

KEY RESPONSIBILITIES:

• Collaborate with business units to understand credit risk-related data elements, including identifying relevant reference data, metadata, and data lineage.
• Analyze source system data and identify derived measures used by the business.
• Develop data definitions and publish data.
• Identify optimal sources for required data variables (e.g., for modeling, calculation, and reporting).
• Investigate data to determine root causes of issues and develop necessary business rules.
• Develop analytical data routines for extraction, alignment, transformation, and preparation for analytical consumption.
• Engineer, design, and optimize data processes within the Analytics Data Layer