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.