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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in data analytics, programming, and machine learning, with a strong focus on attribute development, quality assurance, and responsible AI practices. Proficient in translating business needs into analytical solutions while ensuring data privacy and security.
Highest-signal resume keywords
Python ProgrammingData AnalysisMachine Learning KnowledgeKEL Attribute DevelopmentResponsible AI Practices
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
PythonECLJavaSQLData ManipulationExploratory AnalysisFeature EngineeringData Quality ValidationAnalytical SolutionsAI Prototyping
Soft Skills
Analytical SkillsCreative Problem-SolvingCommunication Skills
Tools & Technologies
Relational DatabasesMachine Learning LibrariesGenerative AI ToolsLarge Language Models
Certifications & Qualifications
Master’s Degree in Data AnalyticsStatisticsData EngineeringComputer ScienceMathematics
Industry Keywords
Data PrivacyData SecurityGovernanceExplainabilityBias Assessment
Tech Stack
Tools & technologiesJavaPythonSQLC++
About the role
Key responsibilities & impact- Develop and maintain KEL attributes from multiple data sources, translating business needs into analytical solutions with Modelling and Technology
- Independently test and monitor attribute quality, completeness, and consistency using Python, ECL, Java, and other tools; diagnose defects and validate fixes
- Maintain attribute definitions, source data documentation, business logic, validation records, user guides, and training materials
- Partner with developers and Technology to deliver attributes into production and improve application functionality, reliability, and efficiency
- Prototype and evaluate AI and machine learning for attribute discovery, feature engineering, and anomaly detection against established methods and defined criteria
- Use approved generative AI and large language model (LLM) tools for coding, testing, and documentation, independently validating outputs before use
- Apply responsible AI practices, including protecting sensitive data, ensuring reproducibility and explainability, assessing bias, documenting limitations, and following governance, security, and human oversight requirements
- Communicate progress, findings, risks, dependencies, and next steps to the manager and stakeholders
Requirements
What you’ll need- Master’s degree in Data Analytics, Statistics, Data Engineering, Computer Science, Mathematics, or equivalent experience
- Experience in programming, data analysis, or a related field, independently delivering moderately complex work and troubleshooting, testing, and documenting fixes
- Experience with KEL, ECL, Python, Java, SQL, or C++, and working knowledge of relational databases, are preferred
- Experience with analytics involving sensitive data and an understanding of privacy, security, and appropriate data handling
- Experience in data manipulation, exploratory analysis, and validation of data quality and analytical results
- Strong analytical, creative problem-solving, and accuracy skills, with the ability to learn and apply new tools and technologies
- Foundational AI and machine learning knowledge, including feature engineering, training, validation, evaluation metrics, overfitting, and data leakage
- Understanding of LLM limitations, output validation, human review, and confidentiality
- Practical experience with Python-based machine learning libraries or approved generative AI tools, and familiarity with responsible AI principles—explainability, fairness, reproducibility, and governance—are preferred
- Strong written and verbal communication skills, with the ability to explain technical concepts and collaborate with technical and business stakeholders
Benefits
Comp & perks- Annual incentive bonus
- Country-specific benefits
- Disability and other accommodation support during the hiring process
