This role is for one of Weekday’s clients
Min Experience: 10+ years
Location: Bengaluru, Karnataka, India
JobType: full-time
We are looking for an experienced and strategic AI Manager / Data Science Leader to drive the development, implementation, and scaling of Artificial Intelligence (AI), Machine Learning (ML), and Data Science initiatives across the organization. The ideal candidate will combine strong technical expertise with business acumen and leadership capabilities to translate complex business challenges into innovative, data-driven solutions. This role requires a proven track record of leading AI teams, managing end-to-end projects, building scalable machine learning solutions, and delivering measurable business outcomes.
Requirements
Key Responsibilities
- AI & Data Science Strategy: Define and execute the organization's AI and Data Science roadmap, identifying opportunities to leverage machine learning, generative AI, automation, and advanced analytics to achieve strategic business objectives.
- Technical Leadership: Lead the design, development, testing, deployment, and optimization of AI/ML models and data-driven applications across multiple business functions.
- Generative AI & LLMs: Drive the adoption of Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI agents, natural language processing (NLP), and other emerging AI technologies to develop intelligent business solutions.
- Team Management: Build, mentor, and lead high-performing teams of AI engineers, data scientists, ML engineers, and analytics professionals. Establish best practices and foster a culture of innovation, collaboration, and continuous learning.
- Model Development & Deployment: Oversee the complete machine learning lifecycle, including data preparation, feature engineering, model training, validation, deployment, monitoring, and continuous improvement.
- MLOps & Infrastructure: Establish scalable AI infrastructure, automated ML pipelines, model monitoring frameworks, and MLOps practices to ensure reliability, performance, and efficient deployment in production environments.
- Business Collaboration: Partner with product, engineering, business, and executive leadership teams to identify use cases, prioritize initiatives, define success metrics, and communicate technical insights in business terms.
- Responsible AI & Governance: Implement frameworks for model explainability, data privacy, security, bias detection, ethical AI, regulatory compliance, and responsible deployment of AI systems.
- Performance & Innovation: Monitor emerging AI trends, evaluate new tools and frameworks, manage project budgets, and ensure AI initiatives deliver measurable improvements in efficiency, revenue, customer experience, and operational performance.
Must-Have Skills
- Strong expertise in Artificial Intelligence, Machine Learning, Data Science, and advanced analytics.
- Proven experience in AI strategy, technical architecture, and end-to-end project delivery.
- Hands-on knowledge of Python, SQL, machine learning frameworks, and statistical modelling.
- Experience with deep learning, NLP, Generative AI, LLMs, and production-grade AI applications.
- Familiarity with cloud AI platforms, data engineering, MLOps, and scalable deployment architectures.
- Strong leadership, stakeholder management, strategic planning, and team-building capabilities.
- Excellent problem-solving, communication, and business decision-making skills.
Good-to-Have Skills
- Experience with cloud platforms such as AWS, Microsoft Azure, or Google Cloud Platform.
- Knowledge of vector databases, prompt engineering, AI agents, and RAG architectures.
- Experience in AI product development, enterprise AI transformation, and technology innovation.
- Understanding of responsible AI frameworks, model governance, and enterprise data security.
Experience & Qualifications
Candidates should have 10–15 years of relevant experience in AI, Machine Learning, Data Science, or related technology domains, including substantial experience in technical leadership or people management. A bachelor's or master's degree in Computer Science, Data Science, Statistics, Mathematics, or a related field is preferred. A strong record of delivering scalable AI solutions and leading cross-functional teams is essential.