Lead - Advance Artificial Intelligence & Machine Learning
Description:
Reporting To: Senior Leadership (AI & Data)
Role Summary
An organization is seeking a highly experienced and forward-thinking professional to lead the development and implementation of advanced machine learning capabilities across large-scale consumer-focused platforms. This role will focus on leveraging both traditional and alternative data sources to enhance decision-making across the customer lifecycle, including acquisition, evaluation, pricing, engagement, and portfolio optimization.
The individual will lead a team of data scientists and machine learning engineers while partnering closely with cross-functional teams including business, risk, technology, and operations. The role will be instrumental in driving scalable, interpretable, and high-impact AI solutions as part of a broader digital and data transformation agenda.
Key Responsibilities
- Lead end-to-end model lifecycle including development, validation, deployment, and monitoring
- Build advanced feature engineering pipelines using structured and unstructured data, including behavioral, transactional, device-level, geospatial, and other non-traditional sources
- Establish experimentation frameworks (including A/B testing) to evaluate model performance, product interventions, and decision strategies with statistical rigor
- Deliver measurable improvements in performance metrics, customer experience, and operational efficiency
- Develop production-grade solutions with strong emphasis on explainability, fairness, robustness, and governance
- Oversee model monitoring practices including drift detection and performance tracking
- Manage and mentor a high-performing team of data scientists and ML engineers
- Provide technical leadership in model architecture, experimentation design, and deployment best practices
- Collaborate with cross-functional stakeholders to translate business needs into scalable AI-driven solutions
- Evaluate and implement emerging approaches such as deep learning, optimization techniques, causal inference, graph analytics, and generative AI where relevant
- Foster a culture of innovation, experimentation, and continuous improvement
Qualifications
- Proven experience building and scaling ML solutions in complex, data-rich environments
- Strong hands-on expertise in model development, feature engineering, experimentation, and deployment
- Solid understanding of statistical modeling, machine learning techniques, and model validation
- Experience with A/B testing, hypothesis testing, and causal analysis frameworks
- Ability to work effectively across business and technology teams in structured environments
- Strong communication, stakeholder management, and leadership skills
Education Requirements
- Research publications or patents are a plus
Preferred Experience
- Exposure to non-traditional or alternative data sources for predictive modeling
- Experience leading teams combining research, engineering, and applied analytics
- Familiarity with responsible AI practices, governance frameworks, and regulatory considerations
Leadership Expectations
- Build, mentor, and retain high-performing technical teams
- Drive high standards of execution, innovation, and measurable impact
- Act as a strategic partner to senior leadership on AI initiatives
- Ensure continued advancement of AI capabilities within the organization
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