The Director of Analytics will set the strategy for the Analytics function within your domain and then set out to deliver results for the business. You will also be responsible for integrating AI into the data acquisition, data dissemination, and analytics process. You will be leading a team of data analysts and data scientists embedded within product teams, empowering the company to make data-driven decisions. The role spans multiple business functions, including sales, marketing, revenue management, supply chain, pricing, workforce management, e-commerce, customer service, and strategic performance. The ideal candidate will have hands-on experience in enterprise-scale analytics, a deep technical understanding of AI and machine learning, and a strong ability to foster and develop high-performing teams.

Key Responsibilities:

• Lead and mentor teams of data analysts and data scientists, ensuring high engagement, career development, and exceptional performance.
• Drive AI-powered data initiatives, including customer segmentation, risk modeling, cost prediction, and operational efficiencies.
• Guide teams in leveraging data lakes, data warehouses, BI tools, and AI/ML models to optimize business processes and decision-making.
• Oversee recruitment, training, and professional development strategies to build a world-class analytics organization.
• Provide strategic input on data architecture, tooling, and best practices for analytics and AI-driven decision-making.
• Stay ahead of industry trends in AI, machine learning, and analytics to keep our teams and strategies competitive.

Qualifications & Experience:

• Bachelor’s degree in Computer Science, Data Science, Statistics, Operational Research, or a related field (Master’s preferred).
• 8-10+ years of experience in analytics, data science, AI/ML, or a related field.
• Strong expertise in applying AI/ML techniques, including experience with LLMs, GPTs, and AI-powered analytics.
• Demonstrated success in managing and scaling analytics teams in a large enterprise.
• Proven experience in enterprise-wide analytics programs, digital transformation, and advanced data modeling.
• Strong background in data engineering concepts, including cloud-based data platforms (AWS, Azure, or GCP).
• Hands-on experience with Python, R, SQL, Tableau, Power BI, and machine learning frameworks.
• Experience with SAFe (Scaled Agile Framework) and Agile product development.
• Familiarity with AWS data and AI services such as SageMaker, Glue, Athena, and Kinesis.
• Strong knowledge of data engineering tools like Kafka, Airflow, and Informatica.
• Understanding of natural language processing (NLP), predictive analytics, and automation.
• Background in leveraging AI to drive operational efficiencies and personalized customer experiences.
• Thought leadership, including conference speaking, industry contributions, or published articles.