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Gartner

Sells research and advice to business leaders

Lead Data Scientist - Multiple Teams

Natural Language Processing & LLMsConfirmed live in the last 24 hours
Full-timeGurugram, Haryana, IndiaNo salary listedIn-person

About the Job

Requirements

  • Proven expertise in Python, Agentic AI, retrieval-augmented generation (RAG) pipelines, large language models (LLMs), natural language processing (NLP), knowledge graphs, and advanced machine learning and deep learning algorithms.
  • Experience utilizing AI technology stacks, including LLMs, workflows, tools or plug-ins, agents, and multi-model capabilities.
  • Expertise with LLM customization techniques, including RAG, tuning, and advanced prompting.
  • Experience analyzing unstructured data and building scalable solutions.
  • Knowledge of model serving, monitoring, and evaluation frameworks.
  • Expertise with vector databases, knowledge databases, embeddings, feature stores, and cloud platforms such as Azure or AWS.
  • Proficiency in prompt engineering, responsible AI practices, and governance, including privacy, auditability, and compliance.
  • Bachelor’s or Master’s degree in Computer Science, Engineering, Statistics, Mathematics, or a related field.
  • At least 8 years of experience in data science, AI, or machine learning roles.
  • At least 6 years of hands-on experience applying machine learning, deep learning, NLP, and LLMs to real-world business problems, including text mining and unstructured data analysis.
  • Expertise in Agentic AI, RAG pipelines, LLMs, prompt engineering, and evaluation frameworks.
  • Knowledge of a wide range of machine learning algorithms, advanced statistics, and natural language processing.
  • Advanced proficiency in Python and SQL, and strong experience with Pandas, NumPy, scikit-learn, TensorFlow, PyTorch, spaCy, and NLTK.
  • Hands-on experience with vector databases such as FAISS or pgvector.
  • Practical experience with AWS, Azure, or GCP for model training, deployment, and scaling.
  • Familiarity with distributed computing using Spark or Databricks.
  • Strong background in data preparation, cleaning, normalization, and handling large-scale unstructured text data.
  • Knowledge of responsible AI, privacy, auditability, and code management using GitHub or Bitbucket.
  • Basic visualization skills using Excel, Power BI, or Streamlit for dashboards and insights.
  • Excellent communication, stakeholder management, problem-solving, and ability to work in fast-paced, milestone-driven environments.

Responsibilities

  • Lead high-impact data science initiatives that convert diverse data into actionable insights and decision support.
  • Design, develop, and implement solutions that drive research excellence, operational efficiency, and revenue growth.
  • Extract, interpret, and visualize insights from large volumes of structured and unstructured data using advanced technologies.
  • Collaborate with stakeholders to design, develop, and implement solutions that deliver insights through machine learning, deep learning, and generative AI techniques.
  • Innovate in text analytics and develop approaches for interpreting complex datasets to deliver recommendations.
  • Own high-visibility programs that translate business objectives into measurable results such as improved engagement, retention, and cost efficiency.
  • Build text analytics and knowledge retrieval capabilities for large-scale unstructured data to generate accurate, explainable insights.
  • Define standards for evaluation, guardrails, prompt engineering, retrieval quality, and hallucination control to ensure trustworthy AI.
  • Enforce best practices in documentation, code reuse, and model lifecycle management while enhancing algorithms to meet evolving needs.
  • Ensure responsible AI practices covering data privacy, intellectual property, safety, and auditability.
  • Mentor and develop a high-performing team of data scientists, fostering a culture of innovation and impact.

About the Company

Gartner

Sells research and advice to business leaders

Gartner sells business and technology research to executives and their teams, along with advice for decisions about strategy, spending, and operations. Clients use its reports, benchmarking tools, and conversations with experts to evaluate vendors, compare practices, and plan investments. Its consulting teams work on technology strategy and complex projects, while conferences bring leaders together for expert sessions and peer discussions. The company earns revenue from research subscriptions, consulting engagements, and conference attendance, serving organizations across many sectors. Gartner was founded in 1979 and is headquartered in Stamford, Connecticut.

Company size
10,001+
Company stage
IPO
Headquarters
Stamford, CT
Founded
1979

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