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Kyndryl

Managed IT infrastructure and cloud services

Data Scientist

Applied Machine LearningConfirmed live in the last 24 hours
Full-timeNo salary listedRemote

About the Job

Requirements

  • Minimum of 10 years of experience in Data Science and Machine Learning, with expertise in Natural Language Processing, Generative Artificial Intelligence, Large Language Models, Machine Learning Operations, optimization techniques, and Artificial Intelligence solution architecture.
  • A PhD in Computer Science, Data Science, or a related field, or equivalent research experience.
  • Experience leading client presentations on proposed solutions.
  • Familiarity with business processes in one to two domains, such as Financial, Telecom, or Retail.
  • Graduate or postgraduate education in computer science, computer engineering, or equivalent, with 10 to 12 years of experience in the IT industry.
  • Experience responding to or developing solutions for requests for proposals, customer proposals, and customer presentations or oral presentations.
  • At least 5 to 6 years of hands-on experience in a Data Scientist or similar role.
  • Strong understanding of Transformers, Large Language Models, fine-tuning, agents, and Retrieval-Augmented Generation techniques.
  • Experience using Large Language Model platforms including OpenAI on Azure, AWS Bedrock, and Google Cloud Vertex AI.
  • Experience in Artificial Intelligence and Machine Learning, focused on Generative Artificial Intelligence and Large Language Models, with experience on Azure, Google Cloud Platform, and Amazon Web Services.
  • Understanding of deploying Large Language Models in cloud and on-premises environments and using application programming interfaces to build industry solutions.
  • Strong domain experience in at least two industries, such as Financial, Retail, Manufacturing, or Telecom.
  • Completion of two to three projects in the domain of expertise.
  • Strong knowledge of Python and C/C++.
  • Data mining, data visualization, and machine learning skills.
  • Fluency in written and spoken English.
  • A degree in a quantitative discipline, such as mathematics, statistics, computer science, or another engineering field.

Responsibilities

  • Lead the development and implementation of Generative Artificial Intelligence and Large Language Model projects in alignment with business objectives.
  • Prepare and present solutions to clients to obtain their approval.
  • Design and deploy Proofs of Concept and Points of View across industry verticals to demonstrate Generative Artificial Intelligence applications.
  • Engage with customers to demonstrate the relevance and impact of Generative Artificial Intelligence applications in their businesses.
  • Collaborate with cross-functional teams to integrate Artificial Intelligence and Machine Learning solutions into cloud environments such as Azure, Google Cloud Platform, and Amazon Web Services.
  • Understand business objectives and requirements, convert them into data problems, and collect and explore data to identify patterns and initial insights.
  • Use statistical and mathematical modeling techniques to create and evaluate models for accuracy, generalization, and business impact.
  • Deploy selected models as code to applications and processes and sustain their business value throughout their lifecycle.
  • Understand business processes, identify issues, and craft solutions across relevant domains.
  • Develop and apply standards and policies for data security, privacy, accuracy, availability, and usability.
  • Perform data management, migration, strategy, change management, and policy and regulation activities.

Desired Qualifications

  • Certification in one or more hyperscaler platforms, including Azure, Amazon Web Services, or Google Cloud Platform.

About the Company

Kyndryl

Managed IT infrastructure and cloud services

Kyndryl provides managed IT infrastructure services for large enterprises, helping them run and modernize their technology environments. Its offerings cover cloud adoption, cybersecurity, security operations, and digital workplace services, all delivered under long-term managed-service contracts. The company works by partnering with major technology providers (including Microsoft) to offer integrated, end-to-end solutions, often complemented by a new security operations center (SOC) and other security capabilities. This focus sets it apart from competitors through scale, enterprise-grade governance, and a history rooted in IBM’s infrastructure services, now independent but aligned with large technology partners. The goal is to support digital transformation by providing reliable, scalable, and secure infrastructure management that enables enterprises to operate efficiently and securely in a cloud-enabled world.

Company size
10,001+
Company stage
IPO
Headquarters
New York City, New York
Founded
2021

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