Job Description Insight Global is seeking an experienced data scientist to deliver insights on a daily basis. The ideal candidate will have mathematical and statistical expertise, a natural curiosity, and a creative mind. While mining, interpreting, and cleaning our data, this person will be relied on to ask questions, connect the dots, and uncover hidden opportunities for realizing the data’s full potential. As part of a team of specialists, the data scientist will “slice and dice” data using various methods and create new visions for the future. Objectives of this role • Collaborate with product design and engineering teams to develop an understanding of needs. • Research and devise innovative statistical models for data analysis, including advanced AI techniques such as LLMs and Agentic AI. • Communicate findings to all stakeholders. • Enable smarter business processes by using analytics for meaningful insights. • Keep current with technical and industry developments, especially in generative AI and autonomous agent systems. Responsibilities • Serve as data strategist to identify and integrate new datasets that can be leveraged through our product capabilities and work closely with the engineering team in the development of data products. • Execute analytical experiments to help solve problems across various domains and industries. • Identify relevant data sources and sets to mine for client business needs and collect large structured and unstructured datasets and variables. • Devise and utilize algorithms and models to mine big-data stores; perform data and error analysis to improve models; clean and validate data for uniformity and accuracy. • Analyze data for trends and patterns and interpret data with clear objectives in mind. • Implement analytical models/machine learning, including LLMs and agentic AI solutions, in production by collaborating with software developers and IT team. • Utilize Azure technologies like Azure Cognitive Technologies, Azure Machine Learning, and Azure Bot Services to design, create, and deploy AI-based applications. • Develop, fine-tune, and deploy large language models and agentic AI systems for automation, knowledge extraction, and conversational AI use cases. • Stay updated with the latest advancements in generative AI, prompt engineering, and autonomous agents. We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to HR@insightglobal.com.To learn more about how we collect, keep, and process your private information, please review Insight Global's Workforce Privacy Policy: https://insightglobal.com/workforce-privacy-policy/. Skills and Requirements • Three or more years of experience in data science or proven experience. • Advanced experience in pattern recognition, predictive modeling, and generative AI (LLMs, transformers, etc.). • Hands-on experience with LLM frameworks (e.g., Hugging Face Transformers, LangChain, OpenAI APIs). • Familiarity with agentic AI concepts and frameworks (e.g., AutoGPT, BabyAGI, CrewAI). • Ability to work effectively in a dynamic, research-oriented group that has several concurrent projects. • Experience in data mining. • Understanding of machine learning, deep learning, and operations research. • Knowledge of R, SQL, and Python; familiarity with Scala, databricks. • Experience using business intelligence tools (e.g., Power BI) and data frameworks (e.g., Azure, SQL Server).