Director of Data Analytics and Data Science
We are seeking an experienced and dynamic Director of Data Analytics and Data Science to lead and grow our data-driven decision-making capabilities. This individual will oversee a team of 10 skilled data analysts, data scientists, and machine learning engineers, driving the strategic vision for our data analytics and science initiatives. The Director will play a pivotal role in shaping our data strategy, ensuring that our data analytics efforts align with business goals and deliver measurable impact across the organization.
Responsibilities:
- Leadership and Strategy: Lead, mentor, and manage a team of 10 data professionals, fostering a collaborative and innovative team culture. Develop and execute a strategic roadmap for data analytics and data science that aligns with the company's business objectives. Advocate for data-driven decision-making across the organization, promoting best practices in data analysis, modeling, and governance. Stay abreast of industry trends and advancements in data science and analytics, applying relevant innovations to the team's work.
- Collaboration and Cross-Functional Partnership: Work closely with the Data Engineering team to ensure that data infrastructure supports the needs of analytics and modeling initiatives. Collaborate with Sales, Marketing, Product, Planning and other key business units to identify opportunities where data insights can drive business value. Partner with executive leadership to translate complex data analyses into clear, actionable insights and strategies. Lead the team in developing predictive models, customer segmentation, and other data-driven strategies to enhance marketing campaigns, sales efforts, and product development.
- Project Management and Execution: Oversee the design, implementation, and delivery of analytics projects, ensuring they are completed on time, within scope, and deliver impactful results. Prioritize and manage multiple projects simultaneously, balancing the needs of different business units with available resources. Ensure data quality, integrity, and security across all analytics projects, adhering to best practices in data governance.
- Performance Monitoring and Reporting: Establish key performance indicators (KPIs) to measure the effectiveness of analytics and data science initiatives. Develop and maintain dashboards, reports, and presentations that communicate insights to stakeholders at all levels of the organization. Regularly review and refine models, methodologies, and processes to ensure they continue to deliver value and drive business performance.
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