AI / ML Data Science Practice Leader

Key Responsibilities :

Strategic Leadership :

Develop and execute the overall AI strategy and roadmap, aligning with business objectives and growth targets.

Project Oversight :

Manage the end-to-end lifecycle of AI projects, from ideation and design to implementation and performance analysis, ensuring timely delivery and alignment with business goals.

Financial Management :

Oversee AI-related budgets, forecasts, and expenditures, ensuring profitability and operational efficiency.

P&L Ownership :

Manage the P&L for AI-related products and services, balancing innovation with cost control to meet financial targets.

Team Leadership :

Lead, mentor, and managing a high-performance team of AI engineers, data scientists, and researchers, fostering a culture of continuous learning and improvement.

Cross-Functional Collaboration :

Work closely with engineering, data analytics, product, and business units to implement AI solutions at scale.

Ethical Compliance :

Ensure the responsible and ethical deployment of AI technologies in accordance with industry standards and regulations.

Innovation Identification :

Identify opportunities for AI innovations that drive growth and operational efficiency.

Stakeholder Communication :

Present AI project outcomes, business impacts, and new opportunities to executive leadership and stakeholders.

External Engagement :

Build and nurture relationships with external partners, vendors, and research institutions to stay at the forefront of AI trends and technologies.

Qualifications : Experience :

Minimum of 20 years IT industry experience with 10+years in AI / technology, with at least 5 years in a leadership or management role.

P&L Management :

Proven experience in managing P&L for technology or AI-driven products / services.

Technical Expertise :

Strong proficiency in AI technologies, including Machine Learning, Deep Learning, Natural Language Processing (NLP), and Computer Vision.

Financial Acumen :

Solid understanding of the commercial and financial aspects of AI projects, including cost management, profitability, and ROI measurement.

Project Delivery :

Experience in scaling AI initiatives and delivering impactful business results.

Communication Skills :

Excellent ability to present complex AI concepts to non-technical stakeholders.

Leadership Skills :

Demonstrated experience in building, motivating, and managing high-performing teams.

Ethical Awareness :

Knowledge of AI ethics, data privacy, and regulatory issues is highly preferred.

Preferred Qualifications :

Educational Background :

Bachelor's or master’s degree in computer science, Engineering, or a related field.

Industry Experience :

Experience in industries such as automotive, healthcare, or retail, where AI-driven personalization and predictive analytics are redefining customer experiences and profitability.

MLOps Knowledge :

Familiarity with MLOps methodologies to streamline the process of moving data-heavy applications from development to robust production deployments.

Cloud Platforms :

Experience with cloud platforms and their integration with AI / ML tools.