Senior Director, Digital Transformation

Lead consulting engagements with top-tier clients in insurance, financial services, and other industries.

Build and maintain strong relationships with stakeholders, ensuring alignment of data initiatives with overarching business strategies and objectives.

Define data transformation strategies, roadmaps, and architectures to modernize data ecosystems.

Advise on best-in-class data platforms, tools, and technologies to enable advanced analytics and data-driven decision-making.

Drive measurable improvements in revenue, cost optimization, risk management, and customer experience through data and analytics solutions.

Establish metrics and KPIs to track the success of transformation initiatives.

Collaborate with data scientists and analytics teams to ensure models and algorithms align with business requirements.

Stay current with AI/ML trends, especially Generative AI and Agentic and Retrieval Augmented Generation (RAG) flows, to advise on cutting-edge applications that unlock new opportunities for clients.

Manage and mentor cross-functional teams, including data engineers, data scientists, and business analysts.

Provide thought leadership and executive-level communication on project status, risks, and mitigation strategies.

Serve as a trusted advisor on modern data and analytics technologies, influencing the broader market perspective.

Participate in industry events, workshops, and conferences to showcase expertise and build brand recognition.

Internal leadership in building capabilities and adoption of modern data and (Gen)AI tools and techniques

Telecommuting permitted more than 50% from local area

Up to 80% unanticipated travel to U.S.-based client sites

Description

Lead consulting engagements with top-tier clients in insurance, financial services, and other industries.

Build and maintain strong relationships with stakeholders, ensuring alignment of data initiatives with overarching business strategies and objectives.

Define data transformation strategies, roadmaps, and architectures to modernize data ecosystems.

Advise on best-in-class data platforms, tools, and technologies to enable advanced analytics and data-driven decision-making.

Drive measurable improvements in revenue, cost optimization, risk management, and customer experience through data and analytics solutions.

Establish metrics and KPIs to track the success of transformation initiatives.

Collaborate with data scientists and analytics teams to ensure models and algorithms align with business requirements.

Stay current with AI/ML trends, especially Generative AI and Agentic and Retrieval Augmented Generation (RAG) flows, to advise on cutting-edge applications that unlock new opportunities for clients.

Manage and mentor cross-functional teams, including data engineers, data scientists, and business analysts.

Provide thought leadership and executive-level communication on project status, risks, and mitigation strategies.

Serve as a trusted advisor on modern data and analytics technologies, influencing the broader market perspective.

Participate in industry events, workshops, and conferences to showcase expertise and build brand recognition.

Internal leadership in building capabilities and adoption of modern data and (Gen)AI tools and techniques

Telecommuting permitted more than 50% from local area

Up to 80% unanticipated travel to U.S.-based client sites

Requirements
Education

Bachelor’s degree, or foreign equivalent, in Computer Science, Information Systems, Data Science, Engineering, Business Analytics, or a related field

Experience
10 years of experience in a data leadership or data transformation-related role.

Special Skills/other Requirements

10 years of experience leading data strategy, analytics, or data governance initiatives

Experience leading data transformation, data management, or data governance initiatives

Experience working within financial services industries (including insurance, banking, or wealth management) or other regulated environments

Experience applying data transformation principles across multiple industries (e.g., retail, healthcare, manufacturing)

Experience working with data architecture, data governance frameworks, and data quality methodologies

Experience with modern data platforms, including data integration, storage, processing, and visualization technologies

Experience working with cloud-based data platforms (e.g., Snowflake, Databricks, BigQuery, or similar)

Experience with data science lifecycle processes, analytics methodologies, or artificial intelligence applications (including generative AI)

Experience presenting data or technology strategies to executive leadership and communicating technical concepts to non-technical stakeholders

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