Marketing Advisor

Job purpose:

Provide expert thought leadership at the enterprise level related to design and implement advanced analytical processes through data/text mining, model development, and prediction to enable informed business decisions. Applies sound analytical expertise to examine structured and unstructured data from multiple disparate sources to provide insights and recommend high-quality solutions to leadership across levels.

Ability to plan and lead initiatives from concept to execution with minimal supervision and communicate results to a broad range of audiences. Effectively use current and emerging technologies to evaluate trends, develop a superior understanding of pricing and revenue management through internal and external sources to creatively solve business problems and come up with innovative methods to problem solving.

Typically uses data, statistical and quantitative analysis, modeling, and fact-based management to drive decision-making. Provides regular expert consultative advice to senior leadership. Effectively shares best practices and fosters knowledge sharing across teams. Provides cross-team and cross-org consultation and supports communities of practice excellence.

Accountabilities:

Leadership:

- Mentors less senior staff

- Lead cross functional projects and programs formally preparing and presenting to management

- Routinely work on multiple highly complex assignments concurrently

- Provides consultation to Sr. Leadership on a regular basis

- Curiosity and inquisitiveness, should be able to reason well and raise pertinent questions

- Intent to learn and try alternate approaches to problem solving

Exploration/Opportunity Identification

- Identifies available data, including internal and external data sources, works with internal and external subject matter experts to select the relevant sources of information

- Explores data sets from a variety of different sources to gather, synthesize and analyze relevant data

- Explores data to refine hypotheses, discover new relationships, insights and analytic paths from the data

- Identifies latest technological advances that accelerate the data analytics of the enterprise

Statistical Analysis & Evaluation:

- Develops design approaches to validate finding(s) or test hypotheses

- Identifies/creates the appropriate algorithms to discover patterns, trends and clusters

- Gathers relevant information, identifies relationships, deduces from cause to effect, and draws logical conclusions

- Finds patterns in the data and finding correlation in related or unrelated variables

- Works in iterative processes with the customer/business partner and validates findings

- Develops innovative and effective approaches to solve analytical problems and communicates results and methodologies

- Develop metrics that can be used to drive business decisions

- Provides analytics expertise in order to solve in depth and technical problems

Presentation/Strategic Recommendations:

- Presenting senior executives with data insights and actionable recommendations with strong storytelling capability

- Helps the business understand the data behind their results in order to gain stakeholder buy-in

- Provides updates and analytical presentations to stakeholders across the enterprise

- Work with business users to assist and teach tools and techniques to the teams while partnering with the business users to solve their business problem

- Provides thought leadership and dependable execution on diverse projects

- Leads discovery process with stakeholders to identify business requirements and expected outcome

- Presents/frames business scenarios in ways that are meaningful and depicts their findings in easy to understand terms

Qualifications & Specifications:

- Relevant experience in analytics/consulting/informatics and statistics

- Key Skills - Data and Business Analytics, Advanced Statistics and Predictive Modelling, Stakeholder Management, Project Management

- Experience in pricing and revenue management - yield management, customer segmentation analytics, revenue impact analytics, etc. is a plus

- Exposure to predictive analytics, ML/ AI techniques is an added advantage

- Education - MBA/Masters in Information Systems, Computer Science, or a quantitative discipline such as mathematics, engineering, operations research, economics & statistics from tier 1/2 institutes

- Tools - Oracle, SQL Server, Teradata, SAS, Python, Tableau/PowerBI/Spotfire

- Good to have - cloud computing, big data, Azure

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