Data Science Architect (Standard) @ Infogain

Core Skills

Key Responsibilities:

Solutioning Presales

Engage with clients and internal stakeholders to understand business problems and propose suitable AI/Analytics solutions.

Participate in RFPs, solution presentations, and client workshops to shape opportunities.

Develop solution blueprints including architecture, technology stack, and delivery approach for AI/ML and data-driven use cases.

Delivery Leadership

Lead and mentor teams of 3-10 members comprising data scientists, data engineers, and analysts.

Oversee end-to-end delivery of AI/Analytics engagements ensuring timelines, quality, and client satisfaction.

Ensure agile delivery practices and governance structures are followed.

Consulting Client Engagement

Act as a trusted advisor to client stakeholders across business and IT.

Conduct AI/ML maturity assessments, PoCs, and roadmap exercises.

Help translate complex data insights into actionable strategies and business impact.

Thought Leadership

Stay updated on emerging AI trends, tools, and techniques.

Create reusable assets, accelerators, and point-of-view documents to drive AI adoption.

Key Requirements:

10-15 years of experience in Data Science, AI/ML, or Analytics space.

Proven experience in pre-sales, solutioning, and stakeholder management.

Hands-on knowledge of AI/ML tools and frameworks (e.g., Python, TensorFlow, PyTorch, Scikit-learn).

Exposure to cloud platforms like AWS, Azure, or GCP.

Strong understanding of data engineering and MLOps concepts.

Excellent communication and presentation skills; able to interact with CxOs.

Prior experience in a consulting firm or in a consulting role is a strong plus.

Ability to lead cross-functional teams and drive outcomes in ambiguous settings.

Preferred Qualifications:

Bachelor s or Master s degree in Computer Science, Data Science, Engineering, or related fields.

Certifications in cloud or AI/ML technologies (e.g., Azure AI Engineer, AWS Machine Learning, etc.)

Exposure to industry-specific AI use cases (Retail, BFSI, Healthcare, etc.)

• 12-14 Years

• Primary Skill: Data Science
• Sub Skill(s): Data Science



• Additional Skill(s): Python, Data Modeling, AI/ML Development, Data Science