About the Company
Capgemini is a global leader in partnering with companies to transform and manage their business by harnessing the power of technology. The Group is guided every day by its purpose of unleashing human energy through technology for an inclusive and sustainable future. It is a responsible and diverse organization of 300,000 team members in nearly 50 countries. With its strong 50-year heritage and deep industry expertise, Capgemini is trusted by its clients to address the entire breadth of their business needs, from strategy and design to operations, driven by the fast evolving and innovative world of cloud, data, AI, connectivity, software, digital engineering, and platforms.
Job Description
Join Capgemini as a Database Cleansing Specialist focused on enhancing AI system performance through meticulous data quality and file management. This is a fully remote position, offering you the flexibility to contribute to cutting-edge AI projects from anywhere within the UK. You will play a critical role in preparing and refining datasets, ensuring the accuracy, consistency, and integrity of data essential for advanced AI model training and deployment. If you have a keen eye for detail and a passion for data quality, we encourage you to apply.
Key Responsibilities
- Perform comprehensive database cleansing to ensure data accuracy, consistency, and completeness for AI model training.
- Identify, correct, and remove corrupt, duplicate, or inaccurate records from large datasets.
- Develop and implement effective file management strategies to organize, store, and maintain extensive data repositories.
- Collaborate closely with AI engineers and data scientists to understand specific data requirements and quality standards for various projects.
- Document all cleansing processes, data sources, transformations, and data quality issues.
- Ensure strict compliance with data governance policies, privacy regulations (e.g., GDPR), and security protocols.
- Contribute to the development and refinement of automated data quality checks and validation rules.
- Monitor data pipelines for anomalies and proactively address potential data quality degradation.
Required Skills
- Proficiency in data manipulation and cleaning tools/languages (e.g., SQL, Python with Pandas/NumPy).
- Strong attention to detail and exceptional analytical and problem-solving skills.
- Proven experience with file management systems, data version control, and data organization principles.
- Solid understanding of relational database structures, data models, and data types.
- Excellent organizational and time management skills, with the ability to work independently and remotely.
- Effective written and verbal communication skills.
Preferred Qualifications
- Bachelor's degree in Computer Science, Data Science, Information Technology, Statistics, or a related quantitative field.
- Familiarity with fundamental AI/Machine Learning concepts and the importance of data preparation for model performance.
- Experience with cloud data platforms and services (e.g., AWS S3/Glue, Azure Data Lake/Data Factory, Google Cloud Storage/Dataproc).
- Knowledge of data governance frameworks and industry best practices for data quality.
Perks & Benefits
- Competitive annual salary and performance-based bonuses.
- Comprehensive health, dental, and vision insurance for you and your family.
- Generous paid time off, including holidays, vacation, and sick leave.
- 100% remote work environment with flexible working hours.
- Opportunities for continuous professional development, training, and certification programs.
- Access to cutting-edge tools, technologies, and innovative AI projects.
- Employee assistance program, wellness initiatives, and mental health support.
- Company pension scheme and life assurance.
How to Apply
If you are interested in this position, please click the "Apply Now" button below. To ensure your application is properly considered, please prepare the following:
- An up-to-date Resume or CV
- A brief cover letter summarizing your experience and motivation
Applications are reviewed on a rolling basis. Only shortlisted candidates will be contacted for an interview.
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