Argentina

Data Science Consultant (La Plata) (Argentina)

Data Science Consultant (La Plata) (Argentina)
Descripción

We are seeking a Data Science Consultant to provide technical leadership and strategic expertise in machine learning and artificial intelligence, guiding the design, development and implementation of advanced ML/AI solutions for our clients.This role connects business needs with innovative AI technologies, ensuring impactful delivery and fostering AI adoption across organizations.ResponsibilitiesProvide technical leadership and strategic direction in ML and AI for client engagementsPlan, design and deliver responsible AI systems and measurement strategies aligned with client objectivesConnect across organizational verticals to drive AI adoption and envision new products, solutions and differentiatorsEngage with clients to understand business challenges and communicate how ML/AI solutions address their needsCollaborate with data scientists and engineers, leading teams as both a peer and mentorMonitor advancements in ML/AI technologies and recommend new approaches considering regulatory impactsAct as liaison between business, legal and technology stakeholders within EPAM and client organizationsShape ML solutions, scope and price engagements, and lead transitions from sales to delivery phasesFoster strong client relationships through effective project delivery, communication and issue resolutionEngage executive and C-level stakeholders to drive enterprise-wide AI adoptionSupport sales and pre-sales activities by assessing data opportunities, responding to RFPs and creating proposalsRequirementsExtensive experience in a leadership role within Data Analytics, Machine Learning and AI (minimum 12 years)Proven track record designing and implementing ML/AI solutionsDeep understanding of machine learning including deep learning, statistics fundamentals, human-computer interaction, CNN/RNN, transformer models, LLMs (RAG), privacy-preserving ML and security fundamentalsDemonstrated experience driving multidisciplinary and geogr
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