Data Understanding Specialist - Data Cycling Center - Spanish Market (KL)

1. Project Readiness, Delivery & Reporting:

• Cooperate with Pillar DUS on project support and requirements. Provide project specific insights, RCA and business metrics. ( Cooperate with XFN's where required, delegated)
• Template application, selection: Work with FA's and DCC on the use, application and criteria for Labeling Template use. ( TCS - JIMU / LP - Neeko )
• SOP Creation / Iteration: Align with RD, BP on requirements, adhere to SOP template. Maintain and update SOP during project lifecycle mapping to any change in requirements or RCA feedback.
• Queue Creation + Injection: Create Live and where required Practice, Test and 2RQA Queues. Across TCS and LP. Liase with FA for support. RD to own complex Queue injections. DUS to support uploading and injection of pre-identified data sets.
• Creation of GDS: Help create, maintain and iterate the Golden Data Set. CS Exam creation linked to GDS.

2. Training and Quality Adherence and Integrity:

• Train, Host or Record SOP review and application. Distribute to internal BD teams. ( LMS - Absorb)
• Monitor the quality of project outputs against KPIs and quality standards, taking corrective actions as necessary to maintain high standards of data accuracy and integrity.
• Queue Health Check: Perform periodic reviews and audits of ongoing projects to identify potential issues or areas for improvement, implementing solutions to enhance project outcomes.

3. Process Optimization and Problem Resolution:

• Identify and address operational challenges or inefficiencies, recommending and implementing process improvements to enhance project flow and compliance with best practices.
• Assist in the training and development of DUS team members to ensure they are equipped to meet project demands and quality expectations.

Qualifications

Minimum qualifications:

1. Fluency in Spanish is required as the role requires communication with Spanish markets & stakeholders, as well as fluency in English as it is the working language.
2. 1-3 years experience in operation for a tech or social media company data analytic experience.
3. Proficiency in data interpretation and analysis; Understanding of AI and Machine Learning concepts, particularly as they relate to data labelling is a plus
4. Excellent verbal and written communication skills for clear and effective communication with both requestors and labelers
5. Strong abilities in simplifying complex instructions and requirements, along with robust experience in training in a technical context
6. Experience in project management with strong organizational skills to manage multiple tasks concurrently, preferably in a data-intensive environment

Preferred qualifications:

1. Excellent problem-solving, task prioritization, follow-up, and quick learning skills.
2. Ability to maintain a high degree of confidentiality while meeting strict deadlines.