Job Description

Role Purpose

The purpose of the role is to define, architect and lead delivery of machine learning and AI solutions.

Do

Demand generation through support in Solution development

Support Go-To-Market strategy

Collaborate with sales, pre-sales &consulting team to assist in creating solutions and propositions for proactive demand generation
Contribute to development solutions, proof of concepts aligned to key offerings to enable solution led sales

Collaborate with different colleges and institutes for recruitment, joint research initiatives and provide data science courses

Revenue generation through Building & operationalizing Machine Learning, Deep Learning solutions

Develop Machine Learning / Deep learning models for decision augmentation or for automation solutions
Collaborate with ML Engineers, Data engineers and IT to evaluate ML deployment options
Integrate model performance management tools into the current business infrastructure

Team Management

Resourcing

Support recruitment process to on-board right resources for the team

Talent Management

Support on boarding and training for the team members to enhance capability & effectiveness
Manage team attrition

Performance Management

Conduct timely performance reviews and provide constructive feedback to own direct reports
Be a role model to team for five habits
Ensure that the Performance Nxt is followed for the entire team

Employee Satisfaction and Engagement

Lead and drive engagement initiatives for the team

Stakeholder Interaction

Stakeholder Type

Stakeholder Identification

Purpose of Interaction

Internal

Practice Head/ Lead

Requirements & inputs to device ML solutions

Sales Team, Pre-Sales, Consulting

Support in defining AI/ML propositions to drive opportunities

Talent Transformation Team, Competency Group

Plan and support delivery of Technical Trainings, knowledge sharing

External

Clients

Deliver client projects and gain trust of client

Academia/ College/Universities

Collaborate on research initiatives, Trainings, Data Science Courses

Display

Lists the competencies required to perform this role effectively:

Functional Competencies/ Skill

Domain/Industry Knowledge - Awareness and knowledge of industry and functional knowledge on the area of work - Foundational
Market Intelligence - Understanding of the practice domain, overall market & competition and nuances of delivery in that domain - Foundational
Systems Thinking - Understanding of the Wipro system (interrelatedness, interdependencies and boundaries) and perform problem solving in a complex environment - Foundational
Leveraging Technology - In-depth knowledge of and mastery over technology domain that commands expert authority respect - Competent
Research Orientation - Knowledge of research methods, relevant theoretical concepts and implementations and experimentation led approach to drive results - Competent

Competency Levels

Foundation

Knowledgeable about the competency requirements. Demonstrates (in parts) frequently with minimal support and guidance.

Competent

Consistently demonstrates the full range of the competency without guidance. Extends the competency to difficult and unknown situations as well.

Expert

Applies the competency in all situations and is serves as a guide to others as well.

Master

Coaches others and builds organizational capability in the competency area. Serves as a key resource for that competency and is recognised within the entire organization.