Nielsen - Manager - Data Science

ROLE DESCRIPTION : 

Designation: Manager

Unit: Nielsen Data Science

Location: Mumbai

JOB DESCRIPTION : 

Scope : 

- Work with Commercial teams, clients and other teams.

- Address client queries through analytics and data deep dives

- Work on Innovation and support revenue generation through Data Science as a Service

Purpose of the role:

The DBL will:

- Conduct training programs for Client Service on the Retail Audit product

- Educate the client on the product by conducting workshops on Coverage etc.

- Pro-active lead and support commercial teams in case of client queries on the quality of the product.

- Build hypothesis - Lead analysis and deep dives related to address product quality issues

- Guide the team to conduct deep dives for clients based on their business problems

- Co-present with the Commercial to re-solve coverage issues for key clients

- Brainstorm on new products for innovation and drive innovation into the business

- Engage with stakeholders within Data Science and across Commercial / PL to address client concerns / to drive innovation

- Create norms database of all coverage and develop thought leadership articles

Main Accountabilities:

- Work on various client needs and issues parallely and ensure integrity of data across clients

- Co-lead client presentations on addressing coverage concerns.

- Deliver all analyses to support client servicing teams on various business issues

- Work on new innovations to help expand the revenue base

- Interact with various Nielsen COEs for coordination and ensure end- to-end implementation of changes

- Build and groom the team

Role Requirements (list the critical experience, knowledge, qualifications, skills, and competencies needed to perform this role - over and above standard Nielsen leadership and personal effectiveness competencies). 

Mark each with E=essential, P=preferred.

- E- Bachelors degree in Statistics, Operations Research, or Econometrics with analytical knowledge

- E - Good communication and presentation skills

- E- Knowledge in Microsoft Excel, Microsoft Powerpoint

- P- Basics in SAS, SPSS, R, Python, Stata or other statistical packages.