Manage end-to-end recruiting across the US and Canada, building candidate pipelines and hiring talent in data engineering, AI, machine learning, and advanced analytics in partnership with hiring teams.
Lead client-facing Life Sciences consulting engagements by translating business needs into project plans and analytical requirements, coordinating offshore delivery, and using SQL and data analysis to support insights.
Leads consulting-services sales to direct clients and develops the Databricks partnership, driving opportunity sourcing, joint solutions, executive alignment, and growth of strategic customer relationships.
Architect and lead enterprise-scale Azure data platforms, setting Microsoft Fabric strategy and delivering secure, governed data pipelines while translating business needs into technical designs and mentoring engineering teams.
Lead pharma analytics consulting engagements by translating client business problems into data science solutions, presenting actionable insights, and helping teams operationalize analytics to drive business value.
Lead the architecture and delivery of production-grade GenAI applications, integrating agentic AI, LLMs, and full-stack features while guiding engineering teams and ensuring scalable, secure enterprise deployments.
Build, evaluate, and deploy generative and agentic AI systems, including multi-agent workflows, fine-tuned language models, and reliability measures that improve performance and reduce hallucinations.
Design and lead enterprise-grade, cloud-native Generative AI platforms on Azure, shaping secure APIs and event-driven systems while guiding architecture decisions across engineering, data, AI, and platform teams.
Build and optimize scalable machine learning and data solutions, translating ambiguous business and analytical needs into reliable production systems across cloud data platforms and distributed processing environments.
Designs, builds, and deploys scalable machine learning and generative AI systems on GCP, owning model pipelines, production inference, monitoring, and the end-to-end ML lifecycle.
Leads enterprise Power BI architecture, governance, and strategy, designing scalable data models and reporting while guiding BI engineers and aligning Azure-based solutions with business needs.
Drive AI and GenAI innovation from opportunity discovery through rapid prototyping and pilot design, collaborating across business, product, and engineering teams to validate user-centered solutions.
Lead technology strategy and client engagement for data and insights transformations, shaping enterprise solutions, advising executives, developing practice capabilities, and mentoring engineering and architecture talent.
Design, develop, and deploy AI solutions for client business problems, collaborating across teams to define requirements, monitor production models, and improve their performance and outcomes.
Designs, builds, and deploys scalable machine learning and generative AI systems on GCP, owning model pipelines, production serving, monitoring, and reliable end-to-end ML workflows.
Architect end-to-end machine learning systems, from cloud-native training and deployment platforms to MLOps practices, partnering with technical and business teams to deliver scalable solutions.
Architect secure, scalable Databricks data and AI platforms, integrating AWS, Snowflake, and Apache Iceberg while establishing governed MLOps, CI/CD, and enterprise AI practices.
Coordinate immigration casework and compliance across the US, Canada, UK, and Spain, partnering with HR, Recruitment, external counsel, and vendors to maintain accurate records and support global mobility operations.
Own full-cycle recruiting, develop hiring strategies, partner with hiring managers, and lead a recruitment team while using hiring data to improve talent acquisition and candidate experience.
Build and operate scalable data platforms and batch and real-time pipelines for GenAI and RAG systems, integrating diverse data sources, retrieval technologies, and cloud infrastructure.
Leads statistical analysis and machine learning projects from conception through deployment, develops client-focused models, and guides teams in delivering actionable data-driven recommendations.
Design and operate scalable MLOps platforms and production ML systems, building deployment pipelines, monitoring model performance, and partnering across engineering and data teams to improve reliability and governance.
Lead analytics consulting engagements by translating client business problems into end-to-end data science solutions, managing project delivery, and communicating actionable insights to senior stakeholders.
Oversee data governance and stewardship by validating data sources, improving data quality, cataloging assets, and aligning business and technical teams on enterprise data standards and IBP requirements.
Page 4 · 99 results
