NOTE:- Candidates who have less than 3 yrs of stay in more than 3 employers will not be shortlisted.

Candidates who are currently not working will not be selected.

Relocation to Jaipur is Mandatory.

Primary Responsibilities -

- Must have practical experience in Machine Learning and have demonstrated utility for the company.

- Be the executive with authority, responsibility and accountability to exploit the value of enterprise information assets and the analytics used to render insights for decision making

- Drive the continual development of enterprise's data and analytics platform - PowerBI for retail, sourcing and corporate areas to make it most user friendly and insightful for management decision making.

- Identify and standardize the use and governance of data and analytics in support of the enterprise's business strategy. This includes the governance of data and algorithms used for analysis, analytical applications and automated decision making.

- Solidify and expand the use of AI and ML in entire enterprise.

Business Accountabilities

- Be the corporate leader of data-driven insights that help support exploitation of strategic and tactical business opportunities, and be a champion for a data-driven, decision-making culture.

- Exploit data using research and analytics to maximize the return on data assets, and develop methods to ensure consistent application and use of analytics.

- Innovate with and expand the organization's research and analytics offerings emerging analytical approaches, skills and technologies such as Artificial Intelligence/ML.

- Identify new kinds, types and sources of data to support business innovation throughout the organization. Define processes for the effective, integrated introduction of new data.

- Be an evangelist for the services and capabilities provided by ACE.

Management and Operational Accountabilities

- Organize and lead a data and analytics center of excellence. Review current job roles, coach and develop existing team members and hire additional capable members to create a team of highly capable data and analytics leaders residing within both retail units and corporate offices.

- Develop VGLs capacity to develop insights with advanced analytics. Further develop data science competencies and resources for the exploitation of big data and sourced data using a combination of open source, cloud and social era tools and techniques for data analytics, machine learning, mining and visualization.

- Lead the development, publication and maintenance of the corporate information architecture that matches and supports business needs.

- Measure master data and reference data for compliance to policy, standards and conceptual models. Assure the deployment and management of data quality monitoring practices.

- Scan the horizon for emerging management tools, skills, techniques and technologies, and ensure their timely introduction for competitive advantage.

- Facilitate the evolution to self-service analytics and data preparation.

Reporting

The Head of Analytics Center of Excellence (ACE) reports directly to Managing Director of VGL.

Staffing

The Head of ACE has an organization consisting of data and analytics leaders, technical professionals, and other specialists who may include the following, either as direct reports or matrixed team members:

- Information stewards

- Data engineers

- Information Architects

- Report designers

- Analytics specialists

- Data scientists

Job Requirements

Education

A bachelor's or master's degree in business administration, computer science, data science, information science or related field, or equivalent work experience. Academic qualification or professional training and experience are also desirable.

Experience

- Must have practical experience in Machine Learning and have demonstrated utility for the company.

- Ten or more years of business experience, ideally in business management, financial or information or IT management recently at or near the executive level. Broad business experience internally and within the vertical industry is desired.

- Five or more years of progressive leadership experience in leading cross-functional teams and enterprise wide programs, operating and influencing effectively across the organization and within complex contexts.

- Experience in integrating complex, cross-corporate processes and information strategies, and/or designing strategic metrics and scorecards.

- Strategy and management consulting experience desirable.

- Retail Industry experience preferred.

Knowledge/Skills

- Must have practical experience in Machine Learning and have demonstrated utility for the company.

- Excellent business acumen and interpersonal skills; able to work across business lines at senior levels to influence and effect change to achieve common goals.

- Demonstrated leadership; proven track record of leading complex, cross functional teams in new endeavors and delivering solutions.

- Proven data literacy the ability to describe business use cases/outcomes, data sources and management concepts, and analytical approaches/options. The ability to translate among the languages used by executive, business, and IT stakeholders.

- Analytical skills: outstanding analytical and problem-solving abilities.

- Familiarity with business information generation and analysis methods.

- Ability to effectively drive business, culture and technology change in a fast paced, complex and global operating environment.

- Excellent oral and written communication skills, including the ability to explain digital concepts and technologies to business leaders, as well as business concepts to technologists; the ability to sell ideas and process internally at all levels

- Proven record of effective leadership, including the ability to balance team and individual responsibilities; building teams and consensus; getting things done through others not directly under his/her supervision; working ethically and with integrity.

- Broad experience desired, but not essential, in multiple domain areas, such as data warehousing, business intelligence (BI), data governance, data architecture, data strategy, data quality management, MDM and enterprise architecture frameworks

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