Col - Siriinfo - Ai Assesor

As an AI Assessor Analyst, you will be responsible for evaluating and assessing the performance, effectiveness, and ethical considerations of artificial intelligence (AI) algorithms and models used within our organization. Your insights and recommendations will play a crucial role in ensuring that our AI solutions meet the highest standards of accuracy, fairness, and transparency.

**Responsibilities**:

- Technical Skills: Proficiency in programming languages (e.g., Python, R) and data manipulation. Familiarity with machine learning frameworks (e.g., TensorFlow, PyTorch) and AI model evaluation techniques.
- Conduct Comprehensive AI Assessments: Evaluate and assess AI algorithms and models to gauge their accuracy, efficiency, and adherence to ethical guidelines. Analyze the algorithms' performance against predefined metrics and benchmarks.
- Ethical Evaluation: Assess the ethical implications of AI algorithms, particularly in areas of privacy, bias, security, and potential societal impacts. Collaborate with relevant stakeholders to address ethical concerns and propose mitigation strategies.
- Data Analysis: Analyze large datasets to identify patterns, trends, and potential biases that may influence the performance of AI models. Ensure data quality and integrity throughout the assessment process.
- Model Validation: Develop and execute tests to validate AI models and algorithms, ensuring they meet the desired criteria and are robust against potential adversarial attacks.
- Documentation: Prepare detailed reports outlining the findings of AI assessments, including recommendations for improvement and potential areas of concern. Present the results to stakeholders in a clear and concise manner.
- Continuous Improvement: Stay updated with the latest advancements in AI technology, industry best practices, and ethical guidelines. Continuously improve the AI assessment framework to reflect evolving standards.
- Collaboration: Collaborate with cross-functional teams, including AI developers, data scientists, and business stakeholders, to understand project requirements and align assessments with business goals.