Meaningful work,
meaningful life

Technical Leadership:

• Lead the design, development, and deployment of machine learning and AI models in real-world environments.

• Drive innovation using supervised, unsupervised, and deep learning algorithms to solve business problems.

• Provide technical direction and hands-on support for Python-based ML development, model evaluation, and data pipelines.

Team & Project Management:

• Manage a team of data scientists, analysts, and ML engineers—mentoring, guiding, and reviewing project progress.

• Define project scope, timelines, and deliverables aligned with business objectives.

• Ensure projects are delivered on time, within scope, and with high quality using Agile/Scrum methodologies.

Business Collaboration:

• Act as the primary point of contact between data science teams and business/product stakeholders.

• Translate business challenges into analytical problems and actionable insights.

• Present insights and technical concepts to executive leadership in a clear, strategic manner.

Strategic Planning:

• Develop the data science roadmap in alignment with broader organizational goals.

• Identify opportunities for AI/ML adoption, automation, and optimization across business processes.

• Evaluate new tools, platforms, and partnerships that can enhance the data science capability.