Are you ready to make an impact? West Monroe is building an AI-native firm. We are looking for a Data Science, Analytics, and Integration Director to join the CIO’s leadership team and shape the next phase of our enterprise data, analytics, and integration capabilities and translate them into measurable business value. The opportunity: This executive will lead the strategy, architecture, and delivery of West Monroe’s internal Data Science, Analytics & Integrations function. Reporting directly to the CIO, the role spans enterprise data platforms, business intelligence, data governance, applied ML and GenAI enablement, and mission-critical integrations across the firm’s core systems. The mandate is straightforward: create trusted enterprise intelligence, accelerate time-to-insight, modernize how data moves across the business, and build an operating model that gives leaders confidence in the metrics they use to run the firm. What you will own: Enterprise data and analytics strategy, including the multi-year roadmap, capability maturity, and investment priorities needed to support an AI-native operating model. Modern data and ML platforms, including Databricks, Azure analytics services, Fabric capacity planning, semantic models, dashboards, and governed self-service analytics. Data governance, stewardship, quality, lineage, and master data practices that improve trust, accountability, and decision quality. Enterprise integrations and API patterns across MuleSoft and adjacent platforms, with a focus on reliability, reuse, observability, and support for critical workflows such as Lead-to-Cash and Hire-to-Retire. A high-performing multidisciplinary team of engineers, analysts, and integration specialists across full-time and nearshore resources. How success will be measured: Establish clear ownership across systems of record, integration layers, and analytics products so stakeholders know where accountability sits. Improve data quality and master data resolution through visible issue management, named owners, service levels, and root-cause prevention. Reduce cycle time from data intake to production insight by standardizing reusable data products, semantic layers, pipelines, and integration patterns. Strengthen executive trust in firmwide dashboards and metrics, reducing dependence on offline spreadsheets and manual reconciliation. Scale applied ML and GenAI in analytics workflows with the right governance, monitoring, and responsible-use controls.
Stand Out From the Crowd
Upload your resume and get instant feedback on how well it matches this job.
Job Type
Full-time
Career Level
Director
Education Level
No Education Listed
Number of Employees
501-1,000 employees