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Nogamy Linkedin · Posted yesterday

Data Scientist

Center District

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Indexed description

Looking for your next challenge in Data Science?


We are looking for a talented Data Scientist to join our team and develop and deploy data-driven solutions using both tabular and textual data. The role combines classic Machine Learning with advanced technologies from the Generative AI space, while working closely with a wide range of business and technology stakeholders across the organization.


Key Responsibilities

  • Lead end-to-end data science projects, from defining the business problem and solution requirements to establishing KPIs, developing models, and deploying solutions to production.
  • Develop and implement Machine Learning and NLP models, including processing text from diverse sources for tasks such as classification, information extraction, and retrieval.
  • Design and build advanced Generative AI solutions, including intelligent Agents and workflows, MCP servers, context management, and RAG architectures.
  • Own model evaluation and observability, including extracting business insights, conducting in-depth error analysis, and monitoring model performance.
  • Work with Big Data and ML infrastructure, including technologies such as Elasticsearch, Kafka, Spark, Redis, and vLLM.
  • Collaborate closely with Data Engineers, Analysts, and domain experts to create scalable solutions that deliver measurable business value.


Requirements

  • 3+ years of experience developing models in Data Science / Machine Learning, with strong hands-on expertise in Classic ML – required.
  • Significant hands-on experience in NLP, including working with open-source models and a strong understanding of Transformers, BERT, LoRA, and SFT – required.
  • 1+ year of proven hands-on experience developing Generative AI agents, including tool calling and prompt optimization techniques – required.
  • 3+ years of professional experience with Python and SQL, with a high level of proficiency – required.
  • Experience taking code to production, including CI/CD, Git, and development/QA/production environments using technologies such as Docker – required.
  • Experience with technologies such as Spark, Elasticsearch, Kafka, Redis, and vLLM – an advantage.
  • Master’s degree in a relevant field – an advantage.
  • Strong self-learning and research skills.
  • Excellent communication and presentation skills, with the ability to present to diverse audiences.
  • Strong critical thinking and analytical problem-solving abilities.


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