The Data Accuracy Specialist is responsible for evaluating and ensuring the quality of data by analyzing and correcting inconsistencies, performing testing, and participating in training sessions. This role involves collaborating with the data team and maintaining quality records while adapting to changing standards.
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1.0 DESCRIPTION
The Data Accuracy Specialist encompasses the daily implementation of various assignments delegated by the client team. This includes engaging in stakeholder meetings and training sessions, all while ensuring the punctual fulfillment of task deadlines.
Responsibilities:
- Evaluate and rate the quality of various types of data based on predefined guidelines and criteria.
- Perform data analysis and preference activities, including but not limited to analyzing responses of different models.
- Perform data and app testing and validation to ensure accuracy and consistency.
- Detect and correct errors, inconsistencies, and inaccuracies in data.
- Provide clear and concise feedback on data quality to assist in continuous improvement.
- Collaborate with the data team to report issues and suggest enhancements to data processes.
- Participate in training sessions to stay updated on rating guidelines and procedures.
- Maintain accurate records of data evaluations and quality assessments.
- Contribute to the development and refinement of data quality assessment methodologies.
- Contribute to the creation of training materials.
2.0 REQUIRED SKILLS/COMPETENCIES
- Exceptional communication skills – being able to communicate important project updates both verbally and in writing
- Excellent Analytical and critical thinking skills – the ability to analyze a situation and plan and implement a solution
- Strong organizational skills and the ability to work under pressure and manage tasks effectively.
- Problem-solving skills – effective analysis and creative solutions for any problems that might arise
- Basic understanding of data concepts and data entry procedures.
- Ability to follow guidelines and instructions accurately.
- Openness to learning and adapting to evolving data quality standards.
- Previous experience in data quality assessment or a related field is a plus.
- Knowledge of specific industry standards or terminology related to data quality is advantageous.
- Comfortable working with data and using relevant software/tools.
3.0 REQUIRED EXPERIENCE AND QUALIFICATIONS
- Minimum Bachelor’s degree or its equivalent.
- Fluency in English (UK) is required, and being a native speaker is an added advantage.
4.0 PREFERRED SKILLS AND EXPERIENCE
- Attention to detail, past experience in delivering QA services or user testing.
- Passion for Large Language Models and related innovations.
- Experience in software/app testing is considered an added advantage.
- Experience working in a multinational/multicultural virtual working environment.
- Experience in working in a cross-functional/matrix organization.
- Fluency in a language other than English is a plus.
Top Skills
Data Analysis
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