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Senior Data Scientist

N-iX

Salary not specified
Dec 22, 2025
Remote, US
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N-iX is seeking a Senior Data Scientist to lead and contribute to data science and AI-centric initiatives, developing advanced analytics solutions and leading short-term projects to help businesses across the globe create next-generation software products.

Requirements

  • 5+ years of experience in data science with a strong focus on machine learning and natural language processing
  • Proficiency in Python and SQL
  • Knowledge of classic Data Science frameworks stack (pandas, numpy, scikit-learn)
  • Familiarity with prompt engineering techniques and LLM agent frameworks (LangChain, LangGraph, LangSmith, Vector Databases)
  • Strong understanding of statistical methods, hypothesis testing, data visualization, and feature engineering best practices (Matplotlib, plotly)
  • Familiarity with MLflow, containerization, and orchestrators
  • Knowledge and hands-on experience with Generative AI, including Prompt Engineering, Fine-Tuning, Automatic Evaluation, and Retrieval-Augmented Generation (RAG) and frameworks (huggingface, ragas)

Responsibilities

  • Develop advanced analytics solutions
  • Lead short-term projects
  • Conduct in-depth data analysis to identify patterns, trends, and insights
  • Set up a testing framework to evaluate agent performance, measure key metrics, and identify optimization opportunities
  • Participate in pre-sales activities that include but are not limited to the preparation of proposals, technical assessments, and implementation of proofs of concept
  • Understand customer challenges and business needs, analyze and estimate requirements, as well as identify the risks involved and provide solutions to them
  • Collaborate with cross-functional teams to define project scope and objectives

Other

  • Master’s or Ph.D. in Data Science, Statistics, Computer Science, or a related field
  • Excellent verbal and written skills in English
  • Strong communication and presentation skills
  • Communicate complex findings to non-technical stakeholders effectively
  • Experience in leading data science projects from conception to deployment