Job description
Top Reasons to work with TDCX
- Attractive remuneration, great perks, and performance incentives
- Comprehensive medical, insurance, or social security coverage
- World-class workspaces
- Engaging activities and recognition programs
- Strong learning and development plans for your career growth
- Positive culture for you to #BeMore at work
- Easy to locate area with direct access to public transport
- Flexible working arrangements
- Be coached and mentored by experts in your field
- Join a global company, winner of hundreds of industry awards
What is your mission
- Structured (breaking down business problems) and Critical Thinking (defining advanced machine learning solutions)
- To drive key initiation that is in tune with the overall data analytic product road map
- To be independent and resourceful in researching and identifying new data sources to expand the current data analytic products
- To continue in creating a unique and useful model validation and risk modelling systems that will be integrated into the day-to-day decision-making process
- Know Human Resources Matrix and ability to identify potential risks and opportunities
- Any other duties and responsibilities that may be assigned to you by the management from time to time, within your category of employment in the organization and for the effective implementation, maintenance and continual improvement of the Quality Management System of TDCX.
Who are we looking for
- Bachelor's degree in a related discipline
- At least 3 - 5 years in Data Analysis/Risk Analysis or Scorecard Reporting systems
- Advance user of tableau, BI Analytic tools, SQL and MS Office would be an advantage
- Experience in analyzing and prediction of Human Resources or Human capital data to resolve business needs or business issues
- Able to demonstrate a high level working in a team, self-starter and willing to learn new tools & analytic environments
- Able to work with key stakeholders to gather the data requirements and business gaps
- Able to advise the stakeholders on the data findings and recommended solutions
