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Leads the development and execution of automated and performance testing solutions. Responsibilities include configuring testing tools and environments, planning test strategies, identifying root causes, reporting defects and results, improving QA processes, supporting audits, and collaborating with product, engineering, project management, and operations teams to deliver high-quality software.

Leads strategic sales planning and commercial growth across product lines, using data and customer insights to improve revenue performance. Manages sales pipelines, builds client relationships, coaches and develops a high-performing team, and drives sales excellence, innovation, collaboration, and continuous improvement across internal and international stakeholders.

Administer and optimize Docebo as the primary technical steward, providing platform support, troubleshooting, configuration, integrations, identity provisioning, automation, documentation, governance, and rollout support. The role partners with Salesforce, HR, security, and technology teams to maintain data integrity, improve reliability, support sales enablement adoption, and scale reusable implementation patterns across global business teams.

Own complex analytics projects from business questions through delivery, developing reliable data products and solutions. Partner with product managers, analytics engineers, technologists, and senior stakeholders to shape data-driven strategy. Apply data preparation, blending, governance, and emerging AI techniques while coaching junior colleagues in analysis design, stakeholder engagement, and project management.

Senior Data Scientist role with no specific responsibilities, qualifications, technologies, compensation, travel, or clearance requirements provided. The posting contains general equal opportunity, privacy, accommodation, benefits, and applicant safety information.

Leads development and production deployment of advanced AI and machine learning models, including LLM, NLP, RAG, and agent-based systems. Designs scalable cloud data and model pipelines, establishes validation and governance practices, conducts experimentation, and monitors model performance. Partners with product and engineering teams on legal analytics, fraud detection, risk scoring, and compliance solutions. Mentors data scientists, presents insights to leadership, and drives strategic AI initiatives.

The job description provides no role-specific responsibilities or qualifications. The position is titled Manager Data Science, suggesting oversight of data science activities, but no further details are available.

Conduct advanced data analysis, statistical modeling, and machine learning experimentation on large datasets, particularly NLP and LLM systems. Develop generative AI solutions, engineer prompts, evaluate RAG approaches, prepare data, visualize insights, and assist with production model deployment. Collaborate with engineers, analysts, and domain experts while documenting models and code and communicating technical findings to stakeholders.

Designs, develops, and supports scalable Salesforce Sales Cloud solutions for sales, operations, and customer success teams. Responsibilities include Apex, LWC, Flow, integrations, customer data management, AI-driven automation, CI/CD, release management, production troubleshooting, and technical leadership. The role requires deep Sales Cloud expertise, API integration experience, Copado, Git, SFDX, and advanced Salesforce automation skills.

Manage and optimize large-scale MySQL production environments, including highly available and disaster recovery architectures. Responsibilities include upgrades, patching, backup and recovery, performance tuning, capacity planning, cloud database support across Azure and AWS, infrastructure automation with Terraform and scripting, observability, incident response, root cause analysis, CI/CD collaboration, and on-call production support.