Analyst - Marketing Analytics - Consulting Firm

Job description :

Analyst - Marketing Analytics

OVERVIEW OF POSITION

- McKinsey's Global Marketing & Sales Practice is looking to fill the role of Analyst at our Marketing & Sales Center of Competence in Gurgaon, India.

- McKinsey's Marketing & Sales practice has a dedicated group, Insights & Analytics, focused on helping clients solve complex business challenges by leveraging insights generated from consumers.

Part of this team focuses on providing deep analytic support, mining large quantities of data, and leveraging sophisticated statistical models to find insight. The team focuses on four specific client service offerings :

- CRM/ CLM Analytics

- Pricing, Promotions

- Assortment Analytics

- Marketing Mix Modeling

- Marketing research survey analytics.

- They have extensive experience in broad range of industries, such as telecom, retail, packaged goods, banking, and consumer durables.

- McKinsey & Co. is looking for a Analyst with deep experience in predictive analytic techniques, which may include propensity modeling, marketing mix modeling, price elasticity modeling, campaign optimization, behavioral segmentation, market basket analyses, Next Product to Buy analytics, etc.

- The Analyst will work directly with client service teams (CSTs.) The Analyst would be located in Gurgaon, India and may travel to serve clients onsite to understand their requirements, and designing / developing solutions.

RESPONSIBILITIES :

The Individual would spend his/her time working with the Insights & Analytics group and consulting teams at McKinsey helping solve analytically complex client problems in the marketing domain, applying and administrating analytical/modeling tools and techniques and drawing managerial insights through statistical techniques and predictive modeling.

Specifically, he/she will be expected to perform the following roles :

- Perform CRM modeling in client engagements for marketing efforts, such as customer segmentation, acquisition and retention, cross-sell/upsell techniques

- Develop statistical models to measure and optimize pricing and marketing campaigns

- Provide expert advice to consulting teams on technique/modeling related issues

- Provide guidance and leadership to teams on analytics projects.

- Support development and maintenance of proprietary McKinsey marketing techniques and other knowledge development projects

KNOWLEDGE & SKILLS REQUIRED :

We are looking for candidates who have demonstrated both a strong business sense and deep understanding of the quantitative foundations of modeling.

Skill Set Required :

Essential :

- Excellent analytical and problem solving skills, including the ability to disaggregate issues, identify root causes and recommend solutions.

- Modeling techniques and specifically logistic Regression, linear regression, cluster analysis, CHAID, market basket analysis, etc.

- Statistical programming software experience in SAS or equivalent, and comfortable working with large data sets. SQL is also preferred

- Industry experience in Financial Services/ Telecom/ Retail is preferred

In addition, candidates must also possess the following hallmarks of excellent problem solving skills, team skills, entrepreneurial ability, and strong communication skills :

- Good written and verbal communication skills. Fluent in both written and spoken English; prior experience in a multi-national environment desirable.

- Energetic, cooperative and pleasant personality. Able to work with and coach effectively a diverse group of team members

- Flexibility, patience, and an understanding of fluid, demanding, and unstructured environments where priorities evolve constantly and methodologies are regularly challenged.

- Ability to work under pressure and deliver on tight deadlines

EDUCATION & PREVIOUS EXPERIENCE REQUIRED :

- Graduate degree in Statistics/Economics/Econometrics/ Engineering/Mathematics (with strong quantitative background).

- 2-3 years of professional work experience with a reputed analytics firm

- Ability to handle data in large volumes (data manipulation, data cleansing and matching) through tools like SAS/SQL