Head of Data Science

As the Head of Data Science for the commercial real estate loan servicing platform, you will play a critical role in leading multiple teams of data scientists in an Agile organization. Your focus will be on driving innovation and ensuring a strong technical foundation for the data science and AI strategy aligned with business objectives. Key Responsibilities: - Strategic Leadership: - Define and execute the data science and AI strategy in alignment with business objectives. - Lead specialized teams in Document Processing and Extraction, Agentic AI, and Predictive Analytics. - Collaborate with engineering and product teams to integrate AI/ML capabilities across the platform. - Stay updated on AI/ML advancements to identify opportunities for competitive advantage. - Team Leadership and Development: - Build and expand data science teams. - Recruit and retain top talent in Generative AI and machine learning. - Develop technical roadmaps for each team based on product priorities. - Encourage an experimental culture with a focus on production-focused ML. - Technical Leadership: - Drive the development of intelligent systems for managing unstructured data. - Create autonomous AI Agents for loan servicing workflows. - Design multi-agent systems for complex tasks. - Ensure explainable, controllable, and business rule-aligned agentic systems. - Develop models for borrower health evaluation and default warning signs. - ML Operations: - Establish MLOps practices for model deployment, monitoring, and evaluation. - Collaborate with engineering to build scalable ML infrastructure. - Implement model governance, testing, and validation frameworks. - Ensure compliance with regulatory requirements and ethical AI standards. Required Qualifications: - PhD or Masters in computer science, statistics, machine learning, or related quantitative field. - 15+ years of data science/ML experience with 8+ years in team leadership. - Proven track record in deploying production ML systems at scale. - Proficiency in modern ML frameworks like PyTorch, Tensorflow, HuggingFace, LangChain. - Experience in predictive modeling and time series forecasting. Preferred Qualifications: - Background in financial services, lending, or real estate technology. - Experience in fintech or SaaS product companies. - Familiarity with commercial real estate data and loan structures. - Knowledge of financial regulations and model risk management. - Track record of building data science functions from the ground up. Key Competencies: - Ability to translate business challenges into ML solutions. - Strong product orientation with a focus on business impact. - Excellent communication skills across technical and non-technical stakeholders. - Strategic thinking paired with hands-on technical skills. - Balancing research innovation with production deployment experience. As the Head of Data Science for the commercial real estate loan servicing platform, you will play a critical role in leading multiple teams of data scientists in an Agile organization. Your focus will be on driving innovation and ensuring a strong technical foundation for the data science and AI strategy aligned with business objectives. Key Responsibilities: - Strategic Leadership: - Define and execute the data science and AI strategy in alignment with business objectives. - Lead specialized teams in Document Processing and Extraction, Agentic AI, and Predictive Analytics. - Collaborate with engineering and product teams to integrate AI/ML capabilities across the platform. - Stay updated on AI/ML advancements to identify opportunities for competitive advantage. - Team Leadership and Development: - Build and expand data science teams. - Recruit and retain top talent in Generative AI and machine learning. - Develop technical roadmaps for each team based on product priorities. - Encourage an experimental culture with a focus on production-focused ML. - Technical Leadership: - Drive the development of intelligent systems for managing unstructured data. - Create autonomous AI Agents for loan servicing workflows. - Design multi-agent systems for complex tasks. - Ensure explainable, controllable, and business rule-aligned agentic systems. - Develop models for borrower health evaluation and default warning signs. - ML Operations: - Establish MLOps practices for model deployment, monitoring, and evaluation. - Collaborate with engineering to build scalable ML infrastructure. - Implement model governance, testing, and validation frameworks. - Ensure compliance with regulatory requirements and ethical AI standards. Required Qualifications: - PhD or Masters in computer science, statistics, machine learning, or related quantitative field. - 15+ years of data science/ML experience with 8+ years in team leadership. - Proven track record in deploying production ML systems at scale. -