Gartner Hiring Drive 2024 For Associate Data Scientist | Location Gurugram

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Gartner Hiring Drive 2024: Gartner Hiring Drive 2024 for its Associate Data Scientist. Gartner Drive organizes off-campus drives for candidates in any batch. To apply, candidates should have a B.Tech/B.E. degree in Any Specialization, Any Graduate. if you are interested, please apply as soon as possible.

Company Name: Gartner

Role: Associate Data Scientist

Location: Gurugram

Experience: 1 – 3 years

Qualification: B.Tech/B.E. in Any Specialization, Any Graduate

Batch: Any

Job Type: Full Time

Salary: 15.5 LPA (Expected)

Gartner Hiring Drive 2024

Job Description:

  • The Associate Data Scientist in the Interaction Insights team will help in generating actionable insights for driving the creation of fact-based research from client interactions and other Gartner internal and external data assets
  • At the core we are looking for a person who is passionate about learning new technologies, text analytics, digging into rows of unstructured data, drawing recommendations & insights, and using creative ways to visualize & interpret it for research
  • This person will have a flair of innovation along with a strong exposure to Python, Data Science, NLP, Machine Learning, Deep Learning, LLMs and the analysis of unstructured data
  • They would be working closely with various stakeholders to explore opportunities to optimize data mining techniques and improve the accuracy of insights generated using NLP or various types of Machine Learning/Deep Learning/LLM models


  • A fresher with a Masters in Engineering, Computer Science, Statistics, Mathematics, Applied Mathematics, Computer Science with focus on AI or Data Science OR BE/BTech or Bachelors + MBA(Data Science) with a minimum of 1-3 years of hands-on AI/ML experience on real-world industry problems, with focus on Text Mining and Natural Language Processing/text analytics.
  • Expertise in Python, SQL. (Pandas, Numpy, scikit-learn, etc), TensorFlow, amongst other data science related tools, libraries.
  • Basic skills in PBI, Excel, Power Point.
  • Code/repo management experience using GitHub/Bitbucket.
  • Ability to train, finetune or apply machine learning/deep learning/LLMs models to business use cases (NLP, LLMs, Supervised, Un-Supervised, Neural Nets, etc.)
  • In-depth NLP knowledge and application experience.
  • Very good hands-on experience of AWS/Azure environment to train, test or deploy the data science models.
  • Own all aspects of accessing and using text data, including data cleaning, data normalization, and data preparation to be used for model training, testing or inference.
  • Analytical bent of mind with the ability to analyze data, identify patterns from unstructured data sets and to draw useful insights / recommendations from them.
  • Critical Thinking & Problem-Solving Skills: Strong analytical skills and the ability to think independently.
  • Eagerness to Learn: Showing strong awareness of the major issues across the IT industry, data science, machine learning and eagerness to learn more.
  • Ability to work in a fast-paced environment and deliver against milestones.
  • Excellent communication skills in technical and business domains
  • Proven ability to influence key stakeholders and leaders.


  • Execute large scale high impact data science projects.
  • Translate research objectives into data & fact-base from Gartner internal and external data assets.
  • Provide ad hoc modeling and analytical insights to inform strategic and operational initiatives.
  • Analyze unstructured text data to find insights and patterns, using advanced data science techniques.
  • Interpret the patterns & insights in-line with the original business objective
  • Solve most pressing business challenges with data science, ML and NLP in the center
  • Interact with internal & external stakeholders to improvise on the findings
  • Work as part of a team in an extremely fast paced work environment with strict SLA s and less turnaround time
  • Be responsible for driving data science driven initiatives with some guidance
  • Develop strong understanding of Tech. industry and expertise in data science domain

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