Data Scientist Lead

Role Purpose

The purpose of the role is to define, architect, and lead the delivery of machine learning (ML) and artificial intelligence (AI) solutions.

Key Responsibilities

Demand Generation

Support solution development by creating and refining AI / ML solutions, contributing to proof-of-concepts, and aligning offerings for solution-led sales. Collaborate with sales, pre-sales, and consulting teams to define AI / ML propositions and drive demand generation. Partner with colleges and institutes for recruitment, joint research initiatives, and delivery of data science courses.

Revenue Generation

Build and operationalize machine learning and deep learning solutions for decision augmentation and automation. Develop and deploy ML / DL models, working closely with ML engineers, data engineers, and IT teams to evaluate deployment options. Integrate model performance management tools into the business infrastructure to ensure continuous improvement.

Team Management

Support recruitment to onboard suitable resources and provide onboarding, training, and skill enhancement opportunities to team members. Manage team attrition, conduct performance reviews, and offer constructive feedback. Act as a role model for organizational values, ensure adherence to performance frameworks, and lead employee engagement initiatives to enhance satisfaction and effectiveness.

Stakeholder Interaction

Internally, collaborate with practice leads for requirements and inputs, and support sales, pre-sales, and consulting teams in defining AI / ML propositions. Work with talent transformation and competency groups to plan and deliver technical training. Externally, engage with clients to deliver projects and establish trust while collaborating with academic institutions on research, training, and data science courses.

Competencies Required

Functional Competencies

Possess foundational knowledge of the domain, industry trends, and market intelligence, with the ability to apply systems thinking for problem-solving in complex environments. Demonstrate competence in leveraging technology and applying research methods to achieve results.

Behavioral Competencies

Exhibit innovation, client-centricity, execution excellence, passion for results, team management, and stakeholder management.

Performance Deliverables

The role requires driving demand generation through successful order booking, delivering revenue through timely project completion, customer success stories, and use cases. It also involves building team capability through training and managing team attrition effectively.

Skills Required

Deep Learning, Machine Learning, Python