ML Lead

ML Lead

 

Role Purpose

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

 

Do

 

1. Demand generation through support in Solution development
   1. Support Go-To-Market strategy
      1. Collaborate with sales, pre-sales &consulting team to assist in creating solutions and propositions for proactive demand generation
      2. Contribute to development solutions, proof of concepts aligned to key offerings to enable solution led sales
   2. Collaborate with different colleges and institutes for recruitment, joint research initiatives and provide data science courses

 

1. Revenue generation through Building & operationalizing Machine Learning, Deep Learning solutions
   1. Develop Machine Learning / Deep learning models for decision augmentation or for automation solutions
   2. Collaborate with ML Engineers, Data engineers and IT to evaluate ML deployment options
   3. Integrate model performance management tools into the current business infrastructure

 

1. Team Management
   1. Resourcing
      1. Support recruitment process to on-board right resources for the team
   2. Talent Management
      1. Support on boarding and training for the team members to enhance capability & effectiveness
      2. Manage team attrition
   3. Performance Management
      1. Conduct timely performance reviews and provide constructive feedback to own direct reports
      2. Be a role model to team for five habits

• Ensure that the Performance Nxt is followed for the entire team

1. Employee Satisfaction and Engagement
   1. 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.

 

• Behavioral Competencies
  • Innovation
  • Client centricity
  • Execution excellence
  • Passion for results
  • Team Management
  • Stakeholder Management

 

Deliver

 

No.	Performance Parameter	Measure
1.	Demand generation	Order booking
2.	Revenue generation through delivery	Timeliness, customer success stories, customer use cases
3.	Capability Building & Team Management	% trained on new skills, Team attrition %

 

Statistical Modeling