Data Science Delivery Lead

Job highlights

• Required Skills (Must have) . Tech . Intermediate to advance knowledge in

A Data Science Delivery Lead, you will oversee project delivery to ensure high quality and client satisfaction, manage client relationships, and lead high-performing teams.

You will be responsible for a wide range of engagements listed below:

Project Delivery:

Accountable for delivery quality for all the projects in the account.
Ensures that client deliverables provide material value or impact to client s businesses, thereby maintaining high levels of contract renewal probabilities.
Ensures process for identifying potential risks are in place. Mentors project leaders in the account to develop strategies to mitigate risks.

Client Relationship:

Builds and maintains strong relationships with clients, understands their needs, manages their expectations, and strives to make them successful in their roles.
Leads Monthly Business Reviews with clients and consciously and regularly seeks feedback from clients on the teams performance.

Team Management:

Builds and leads high-performing project teams. Provides guidance, mentoring, and coaching to team members. Promotes a culture of collaboration, innovation, and continuous learning.
Provides both business and technical guidance to the delivery team.
Looks for improvements in delivery processes, actively seeks buy-in on the improvements from peers and managers, implements them in the team and monitors their adoption.
Ensures that necessary structures, processes, KPIs, scorecards, etc., to ensure quality delivery standards, are adopted as a way of working by everyone in the account.

Business Consulting:

Engages clients in strategic conversations shows thought leadership.
Manages account delivery within the financial levers that help maintain EBITDA. These levers include Gross utilization, recommended designation mix, and billing Project delivery leads where possible.

Required Skills (Must have)

Tech

Intermediate to advance knowledge in
Project management methodologies and tools
Probability and Statistics
Practical Machine Learning, including key pitfalls and approaches to address them.
SQL and Python
MS Office applications - Excel and PowerPoint

Non-Tech

Strong business acumen with an ability to assess financial impact of decisions - both in the operations of running the delivery team and in the context of delivering solutions to clients.
Ability to recognize pragmatic alternatives vis- -vis a perfect solution and get the delivery teams on-board to pursue them, balancing priorities of time with potential business impact.
Strong people skills, including conflict resolution, empathy, communication, listening, and negotiation.
Leadership and mentorship to the delivery team.
Ability to storyboard presentations effectively and hold conversations with senior executives in client businesses.
Self-driven with a strong sense of ownership.
Solution proposals, collaborating with growth, customer success and central solutioning functions.
Ability to hold conversations with senior and C-suite level executives in client businesses.