Our client is looking for a visionary leader to join their team as the Vice President of Data & Analytics.
ROLE OVERVIEW:
Develop and execute a forward-thinking, scalable data strategy to drive commercialization of data and insights. Lead efforts to monetize data assets, establish a robust framework for data governance, and advance analytics capabilities. Collaborate with C-level executives and cross-functional business leaders to position data as a critical enabler for business growth and operational optimization.
KEY QUALIFICATIONS AND EXPERIENCE:
- 10-15 years of progressive experience in data management, analytics, or related fields, with at least 5 years in senior leadership roles.
- Proven track record of driving the commercialization of data assets and delivering measurable business value through data-driven initiatives.
- Bachelor's Degree in Data Science, Analytics, Computer Science, Statistics, or a related field; MBA is highly desirable.
- Expertise in developing and executing data architecture and governance frameworks that align with industry best practices and regulatory requirements.
SPECIFIC & BUSINESS KNOWLEDGE REQUIRED:
- Strong understanding of Data Management Body of Knowledge (DMBOK), data architecture, and administration.
- Proficiency with industry-standard data analytics tools and programming languages such as SQL, Python, R, Tableau, and Power BI.
- Expertise in advanced query optimization, data visualization, and best practices in data processing and analytics.
- Deep knowledge of data management processes, governance standards, data warehousing, and data integration principles.
KEY RESPONSIBILITIES:
- Develop and Execute Data & Analytics Strategy:
- Formulate and drive a comprehensive data and analytics strategy to optimize data value through commercialization and insights generation.
- Align data initiatives with broader company goals to identify market opportunities and provide a competitive edge.
- Develop KPIs and performance metrics derived from data insights to drive strategic decision-making.
- Architect and Implement Scalable Data Infrastructure:
- Design and implement a scalable, modern data infrastructure supporting advanced analytics capabilities such as machine learning, predictive modelling, and real-time analytics.
- Oversee seamless data integration across multiple platforms to ensure high-quality, accessible data.
- Ensure infrastructure scalability for future data expansion and innovation needs.
- Lead Advanced Analytics Development:
- Design and deploy advanced analytics solutions, including BI systems, machine learning models, and predictive analytics.
- Empower business units with actionable insights to boost decision-making and business outcomes.
- Collaborate with C-Level and Business Leaders:
- Serve as a strategic partner to C-level executives and business leaders, aligning data initiatives with business objectives.
- Present insights, forecasts, and data-driven recommendations to the executive team to support strategic initiatives.
- Drive Data Creation for Strategic Initiatives:
- Lead efforts to create and refine datasets for POCs, simulations, and forecasts critical for C-Suite decision-making.
- Contribute to business process improvements through data-driven insights and operational forecasting.
- Ensure Data Governance and Compliance:
- Establish and enforce data governance policies and best practices to maintain data quality, integrity, and security.
- Ensure compliance with applicable regulations.
- Oversee Data Integration and Structuring:
- Manage the integration and structuring of data from various sources for optimal analysis and reporting.
- Transform raw data into structured formats for easy access to relevant insights.
- Develop and manage the department's budget, aligning it with the overall company strategy.
- Make informed decisions on short-term projects and long-term investments in data infrastructure, analytics tools, and human capital.
- People Management & Development:
- Lead and mentor a team of 5-10 senior managers, with indirect responsibility for a larger extended team of 50+ professionals.
- Establish clear expectations, provide direction, and foster a high-performance culture.
- Ensure continuous development and alignment with strategic priorities.
- Stay at the forefront of data monetization, analytics, and emerging technologies such as AI, ML, and automation.
- Champion the adoption of cutting-edge tools, methods, and best practices to drive operational efficiency and continuous innovation in data processing and analytics.
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