AI Chapter Lead - ödənişlər biznesi

Ümumi məlumat
We are seeking a hands-on AI Chapter Lead to drive the delivery of AI use cases and ensure technical excellence within our AI team. This role focuses on leading a team of data scientists, ensuring projects are delivered on time with high quality, and fostering the technical growth of team members. The ideal candidate combines strong technical depth with delivery focus—someone who can roll up their sleeves when needed while guiding the team through complex implementations.
Öhdəliklər
AI Use Case Delivery
Own end-to-end delivery of assigned AI use cases, ensuring projects progress from development through deployment with clear timelines
Manage sprint planning, task allocation, and daily stand-ups to maintain delivery momentum
Remove technical blockers, coordinate with dependent teams (IT, Data Engineering), and escalate issues proactively
Ensure quality standards through code reviews, testing practices, and documentation requirements
Technical Leadership
Provide hands-on technical guidance on model development, feature engineering, and deployment approaches
Establish and enforce coding standards, version control practices, and MLOps workflows
Lead technical design discussions and architecture decisions for use cases within scope
Stay current with ML/AI advancements and introduce relevant techniques to the team
Team Development
Mentor and coach data scientists, providing regular feedback and career guidance
Conduct technical skill assessments and create individual development plans
Organize knowledge sharing sessions, tech talks, and learning initiatives within the chapter
Support hiring processes including technical interviews and candidate evaluation
Model Operations & Monitoring
Ensure deployed models meet performance standards through monitoring and alerting frameworks
Coordinate model retraining cycles and performance optimization efforts
Maintain documentation standards for model handover and operational support
Collaborate with Model Validation team on documentation requirements and review processes
Stakeholder Coordination
Serve as primary point of contact for business stakeholders on delivery status and technical feasibility
Translate business requirements into technical specifications for the team

• Coordinate with platform team on infrastructure and tooling requirements
  

Tələblər
Education & Experience
Master's degree in Data Science, Statistics, Computer Science, Mathematics, or related quantitative field
4+ years of experience in data science/ML engineering, with minimum 1 years in a lead or senior technical role
Experience In Banking/financial Services Is Strongly Preferred
Track record of delivering ML projects to production
Technical Skills
Strong proficiency in Python and SQL
Solid knowledge of ML algorithms: regression, classification, clustering, ensemble methods, deep learning fundamentals
Hands-on Experience With ML Platforms (Dataiku Preferred)
Understanding of MLOps practices: CI/CD for ML, model versioning, monitoring, containerization
Experience With Cloud Platforms (MS Azure Preferred)
Familiarity with Git, Docker, and API development
Demonstrated ability to lead small technical teams and deliver results
Strong mentoring and coaching capabilities
Clear communication skills—ability to explain technical concepts to non-technical stakeholders
Proactive problem-solver with strong ownership mentality
Collaborative approach with attention to quality and detail
Experience with LLMs, RAG architectures, or conversational AI implementations
Familiarity with model validation processes and regulatory documentation requirements
Experience with Agile/Scrum methodologies in data science context
Background in NLP or computer vision projects