.About this RoleThe 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 for innovation along with a strong exposure to Python, Data Science, NLP, Machine Learning, Deep Learning, LLMs, and the analysis of unstructured data.What You'll DoExecute 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 a strong understanding of the Tech industry and expertise in the data science domain.What You'll NeedA 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
