Gartner Data Scientist Job Openings 2025 – Apply Soon!

Qualifications

What you’ll need :

• BS/MS/PhD in Computer Science or other technology, Math, Physics, Statistics or Economics (focus on Natural Language Processing, Information Retrieval a plus)
• 1+ years’ experience in data science methodologies as applied to live initiatives or software development
• 1+ years of experience in python coding and statistical analysis
• Working experience in several of the following:
  • Prompt Engineering and working with LLMs
  • Machine Learning and statistical techniques
  • Data mining and recommendation systems
  • Natural Language Processing and Information Retrieval
  • Handling large volumes of data
  • User behavior modeling

About this role :

• In Gartner’s Services Data Science team, we innovate the way our team helps clients receive value, so technology leaders will be able to make smarter decisions in a different way.
• Gartner is searching for a talented associate data scientist to join our team. You will have access to the best facilities, technology and expertise within the industry and will work on challenging business problems.
• This is an excellent opportunity to be part of a new venture, in a start-up environment where you can truly develop your skill set and knowledge and bring impact to the team.

What you’ll do :

Here is a sample of some initiatives that our associate data scientists work on —

• Designing and implementing state of the art Large Language Model (LLM) based agents that seamlessly synthesize complex information and initiate important actions in a business workflow.
• Using NLP models and advanced Generative AI techniques to derive actionable insights from unstructured text data, such as call transcripts and emails. Evaluating the performance of the models, continuously optimizing them for better accuracy and relevance
• Building various recommendation tools like client interest predictor and personalized content recommenders to drive higher client value delivery
• Develop customer churn prediction models that proactively identify at-risk clients, leverage statistical and machine learning techniques to extract actionable insights from client retention data.
• Build tools to process structured and unstructured data
• Engineering features and signals to train ML model from diverse data collection
• Collaborate with cross-functional teams to integrate data science solutions into existing systems and user workflows, ensuring seamless data accessibility and usability.