Vice President, Data Scientist, AI Risk

In a world of disruption and increasingly complex business challenges, our professionals bring truth into focus with the Kroll Lens. Our sharp analytical skills, paired with the latest technology, allow us to give our clients clarity—not just answers—in all areas of business. We embrace diverse backgrounds and global perspectives, and we cultivate diversity by respecting, including, and valuing one another. As part of One team, One Kroll, you’ll contribute to a supportive and collaborative work environment that empowers you to excel. 

Kroll’s Cyber Risk team works on over 2,000 cases a year, including some of the most complex and highest profile matters in the world. With experts based around the world, supported by ground-breaking technology, we help protect our client’s data, people, operations and reputation with innovative assessments, investigations, and intelligence. We are the only company in the world with the expertise and resources to deliver global, end-to-end cyber risk management, supporting organizations through every step of their journey toward cyber resilience. 

Job Summary: 

The ideal candidate will possess a strong foundation in data science and machine learning with an ability to understand technical model components, and curiosity about the business of our clients. An understanding or awareness of relevant legal and regulatory frameworks is helpful. We are seeking a highly skilled Data Scientist with expertise in Artificial Intelligence (AI) and Machine Learning (ML) model validation to join our team. This role is critical in helping our clients ensure the accuracy, reliability, and compliance of AI/ML solutions.  

Day-to-day responsibilities:

• Model Examination and Validation: Design, develop, and implement methods and processed to validate AI/ML models to ensure they meet the required standards for accuracy, performance and compliance.
• Explainability and Transparency: Develop methods and leverage available technology and toolsets to explain AI/ML model decisions and ensure transparency in model outputs. 
• Compliance and Ethics: Ensure AI/ML models adhere to legal, ethical, and regulatory standards, including data privacy and bias mitigation. 
• Documentation: Maintain comprehensive documentation of model development processes, validation results, and compliance measures. 
• Continuous Improvement: Stay updated with the latest advancements in AI/ML, and continuously improve model validation techniques. 
• Technical Expertise: Utilize data science knowledge to understand, examine, and audit technical model components. This includes applying machine learning techniques, statistical analysis, predictive modeling, and data visualization to interpret data, analyze results, and provide insights. 
• Programming and Testing: Develop and test code using programming languages such as SQL, Java, C++, Python, and apply appropriate testing methods. Validate analytical models, employing model fit testing, tuning, and validation techniques to assess accuracy and robustness of models. 
• Compliance Controls: Develop and implement effective controls to ensure compliance with established policies and regulations. Monitor the effectiveness of controls, making necessary adjustments and improvements. 
• Audits and Risk Assessments: Conduct risk assessments of AI/ML models and methods to ensure compliance and identify areas of concern. Stay current with changes in regulations and industry standards, and update policies and procedures accordingly. 
• Collaboration: Work closely with cross-functional teams, solution engineers, subject matter experts, compliance professionals, and business stakeholders, to integrate AI solutions into business processes.  

 Essential traits:

• Education: Bachelor’s or Master’s degree in Data Science, Statistics, Computer Science, or a related field. A Master’s or Ph.D. in Data Science is preferred. 
• Experience: Minimum of 3-5 years of experience in data science, with a focus on AI model development, testing, training, tuning, and validation. 
• Technical Skills: Proficiency in programming languages such as Python or R, and experience with machine learning frameworks like TensorFlow, PyTorch, or scikit-learn. 
• Analytical Skills: Strong understanding of data analysis, modeling, and interpretation. 
• Compliance Knowledge: Knowledge of compliance standards and regulations relevant to emerging technology. 
• Communication Skills: Excellent written and verbal communication skills. 
• Organizational Skills: Strong organizational and project management skills. 
• Independence: Ability to work independently and make informed decisions. 
• Problem-Solving: Strong problem-solving skills and attention to detail. 

Kroll is committed to equal opportunity and diversity, and recruits people based on merit.

In order to be considered for a position, you must formally apply via careers.kroll.com.

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