Lead - AI ML Generative AI

Lead - AI ML Generative AI:

Key Responsibilities

• Leadership and Team Management: Lead, mentor, and manage a team of AI/ML engineers and data scientists, fostering a collaborative and high-performance culture.
• Strategy Development: Develop and implement AI/ML strategies aligned with the company's business goals and objectives.
• AI/ML Solutions: Design, develop, and deploy AI and machine learning models to solve complex problems in underwriting, claims processing, fraud detection, customer service, and personalized marketing.
• Generative AI: Explore and implement generative AI techniques to create novel solutions for product development, risk assessment, and customer engagement.
• Data Management: Oversee the collection, preprocessing, and analysis of large datasets to ensure data quality and integrity.
• Stakeholder Collaboration: Work closely with cross-functional teams, including product managers, actuaries, and IT departments, to ensure successful integration and adoption of AI/ML solutions.
• Research and Innovation: Stay updated with the latest advancements in AI/ML and generative AI, and drive continuous innovation within the team.
• Compliance and Ethics: Ensure all AI/ML solutions comply with industry regulations and ethical standards.
• Performance Monitoring: Implement monitoring and evaluation frameworks to assess the impact and performance of AI/ML models.

Innovation & POC Development

• Lead the development and execution of innovative analytics solutions and Proof-of-Concept (POC) projects.
• Collaborate with cross-functional teams to identify impactful use cases and prototype solutions.

Business Alignment & Outcome Metrics

• Work with business stakeholders to establish success metrics and key performance indicators (KPIs) for analytics initiatives.
• Ensure analytics solutions align with strategic business objectives and regulatory requirements.

POC Adoption & Change Management

• Promote the transition of successful POCs into production environments.
• Develop and implement change management strategies to secure stakeholder support and ongoing usage.

Technical Leadership & Team Oversight

• Provide technical guidance and mentorship to data scientists and analysts.
• Review and approve analytical models, code, and methodologies to ensure their robustness and scalability.

Strategic Research & Future Tech Exploration

• Stay informed about emerging technologies in AI/ML, GenAI, and other relevant future tech for the insurance industry.
• Conduct strategic research and feasibility studies to evaluate potential applications and business impact.

Qualifications

• Education: Masters in Computer Science, Data Science, Machine Learning, or a related field.
• Experience: Minimum of 5 years of experience in AI/ML, with at least 3 years in a leadership role.
• Technical Skills: Proficiency in programming languages such as Python, R, and Java; experience with AI/ML frameworks such as TensorFlow, PyTorch, and scikit-learn.
• Cloud Tech : Azure, GCP , AWS . Preferable is Azure
• Domain Knowledge: Expertise in the insurance domain, with a strong understanding of industry-specific challenges and opportunities.
• Analytical Skills: Strong problem-solving skills with the ability to analyze complex data and generate actionable insights.
• Communication Skills: Excellent communication and interpersonal skills, with the ability to convey technical concepts to non-technical stakeholders.
• Project Management: Demonstrated experience in managing large-scale AI/ML projects from conception to deployment.
• Innovation: Proven track record of driving innovation and staying abreast of emerging technologies in AI/ML and generative AI.