
Modelling & Data Science Director
2 weeks ago
The purpose of this role is to develop best in class strategies and management of all Insights and Analysis activity on assigned clients, to manage and develop the team and serve as a point of escalation as needed.
Job Description:
Key Responsibilities
Team Leadership & Management
Lead and manage a team of 5-10 AI engineers, ML engineers, and data scientists
Conduct performance reviews, provide mentoring, and support career development
Foster a collaborative culture focused on innovation and continuous learning
Manage team workload distribution and resource allocation
Technical Leadership
Design and develop AI models and algorithms from scratch. Implement AI solutions that integrate with existing business systems to enhance functionality and user interaction
Provide technical guidance on AI architecture, model selection, and implementation strategies
Review code, ensure best practices, and maintain high technical standards
Drive technical decision-making for AI platform architecture and tooling
Stay current with AI/ML trends and evaluate new technologies for adoption
Project Management & Delivery
Plan, execute, and deliver AI projects from conception to production deployment
Coordinate cross-functional initiatives with product, engineering, and business teams
Manage project timelines, budgets, and resource requirements
Ensure AI solutions meet scalability, performance, and reliability standards
Implement and maintain CI/CD pipelines for ML model deployment
Strategic Planning & Innovation
Develop AI engineering roadmaps aligned with business objectives
Identify opportunities to leverage AI for business value and competitive advantage
Establish engineering best practices, coding standards, and quality assurance processes
Drive innovation initiatives and research into emerging AI technologies
Contribute to AI strategy discussions with senior leadership
Required Technical Skills
AI/ML Expertise
Python
Strong background in machine learning algorithms, deep learning, and neural networks
Experience with ML frameworks: TensorFlow, PyTorch, scikit-learn, Keras
Knowledge of computer vision, NLP, and statistical modeling techniques
Data Engineering & Infrastructure
Experience with data pipeline development and ETL processes
Knowledge of big data technologies (Spark, Hadoop, Kafka)
Understanding of database systems (SQL, NoSQL, vector databases)
Data preprocessing, feature engineering, and data quality management
Cloud & DevOps
Experience with cloud platforms (AWS, Azure, GCP) for AI/ML workloads
MLOps tools and practices for model lifecycle management
Containerization and orchestration (Docker, Kubernetes)
Continuous Deployment (CD)
Experience Requirements
8+ years of AI/ML engineering experience with hands-on model development and deployment
3+ years of team leadership or technical management experience
Proven track record of delivering production AI systems at scale
Experience managing the complete ML lifecycle from research to production
Background in both individual contribution and team collaboration
Location:
Bengaluru
Brand:
Merkle
Time Type:
Full time
Contract Type:
Permanent
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