Responsible for designing and deploying machine learning models, collaborating with teams, ensuring data quality, mentoring, and leading technical initiatives.

The Senior Data Scientist will design and build scalable data products, develop machine learning models, and collaborate with various teams to drive impactful data solutions.

The role involves designing, deploying machine learning models, collaborating with teams, ensuring data quality, monitoring model performance, and mentoring junior staff.

Seeking a Senior Data Scientist to design and build scalable data products, develop machine learning models, and mentor junior staff while promoting data quality and collaboration.

As a Data Engineer, you will build data pipelines and scalable architectures for Generative AI, collaborating with ML Engineers and implementing best practices.

Support senior consultants on client projects: gather requirements, run interviews and workshops, build and present data-driven strategic recommendations, deliver trainings, propose client support, and help produce research and content.

Lead AI-driven client engagements: define project scope, develop AI and data strategies, perform advanced analysis, present recommendations, collaborate with data teams, and develop business opportunities.

The Accounting Specialist at Artefact manages day-to-day financial operations including accounts receivable, accounts payable, month-end close, project accounting, and intercompany coordination.

Lead multidisciplinary teams to deliver AI and data transformation projects, develop client portfolios, drive sales and proposals, ensure high-quality delivery, and spread consulting knowledge across the firm.

As an AI Engineer, you will build and deploy AI solutions, develop machine learning models, and collaborate with clients on technical designs and innovations.

As a Project Manager, you'll develop strategies, solve complex problems with data and AI, manage projects, and engage with clients to drive strategic initiatives.

As a Senior Consultant, you'll develop strategies, solve complex problems, deliver projects, engage clients, and contribute to business growth through data and AI expertise.

Seeking a skilled Data Engineer with Apache Airflow experience to design, build, and maintain scalable data pipelines, optimize ETL processes, and provide technical leadership while collaborating with cross-functional teams.

As a Data Science Manager, you lead a team, manage data-driven marketing projects, enhance team competencies, and engage with C-level clients to drive business transformations.

Lead transformational data projects in marketing, develop innovative solutions, improve marketing analytics, build client relationships, mentor junior team members, and ensure quality deliverables.

Lead client engagements on AI strategy and data transformation, working with C-level stakeholders to define governance, roadmaps, and impact-driven programs. Break down ambiguous problems into structured recommendations, run workshops, align technical delivery with business objectives, and contribute to offer development and thought leadership.

Lead marketing-focused data science projects, build end-to-end ML solutions (attribution, MMM, campaign optimization), mentor junior team members, collaborate with consultants and engineers, and improve Artefact's internal tooling and MLOps practices to deliver high-quality client outcomes.

Lead end-to-end development of GenAI web applications, integrate ML models, manage prompt/context and vector DBs, configure agent orchestration, mentor developers, engage clients, and oversee cloud deployments and CI/CD.

Lead data and AI transformation engagements: define AI and data strategies, advise C-level clients, manage cross-functional teams, drive business development, ensure solution adoption, and contribute to thought leadership and internal training.

Lead design and implementation of scalable, reliable software systems for GenAI/LLM projects. Deploy and optimize applications using Docker, Kubernetes, Terraform, and cloud platforms. Manage multidisciplinary teams and client engagements, establish engineering best practices, and integrate emerging technologies to ensure high-quality, performant AI-powered systems.