Developing AI Skills To Improve Business Operations
Anjali Kabra, MS’24, information systems, honed her AI skills on a co-op at Emergys and in the classroom to prepare for a career that focuses on using AI to optimize business operations.
With a co-op experience at Emergys and hands-on classroom learning, Anjali Kabra, MS’24, information systems, is ready to pursue a career in business operations using the many skills she had learned in AI development.
Kabra completed a co-op as a CX data analyst at Emergys, an experience she considers transformative. She worked on a generative AI platform that was designed to streamline procurement. Kabra’s work focused on selecting, fine-tuning, and training machine learning models for real-time data retrieval and validation. She used industry standard tools such as Python, OpenAI’s GPT models, and Azure. By automating information extraction and optimizing the procurement process, Kabra was responsible for a 30% efficiency increase in the procurement process, which benefitted more than 1,000 users.
She also had the opportunity to develop intelligent chatbots and automate content generation, which enhanced data retrieval accuracy through innovative AI models and NLP techniques.
She attributes the project’s success to her close collaboration with cross-functional teams, where regular briefings and alignment sessions ensured that the solutions were not only technically sound but also addressed business needs. Through this experience, she observed the power of AI-driven automation in reducing manual tasks and supporting agile decision-making, a takeaway she considers essential for any business seeking to optimize operations.
During her co-op, she tackled significant data challenges. Working with large datasets required meticulous data wrangling and SQL manipulation to ensure data integrity. Employing advanced visualization tools like Tableau, Power BI, and Databricks, she presented complex insights in accessible formats. The structured data pipelines she developed enabled stakeholders to make real-time, data-driven decisions, transforming raw information into actionable insights that improved overall business intelligence. Kabra’s use of natural language processing (NPL) and generative AI techniques facilitated the swift translation of data into strategic information that informed choices, underscoring her ability to bridge technical solutions with business impact.
Reflecting on her academic journey, Kabra attributes her coursework at Northeastern in data management, machine learning, financial technology, and advanced data science as being instrumental in preparing her for real-world environments.
She also worked for the academic department, contributing to her professional development by enhancing her communication and time-management skills. These experiences taught her to manage responsibilities and engage with diverse audiences, valuable lessons that enriched her interactions with stakeholders at Emergys.
Prior to attending Northeastern, Kabra completed an internship at Microsoft, which introduced her to cloud-based systems and data-driven technologies. This experience sparked her passion for AI and data science and influenced her decision to pursue a master’s degree in information systems.
Kabra envisions a future dedicated to advancing AI-driven solutions in healthcare, supply chain management and finance, leveraging deep learning, NLP, and cloud automation to drive operational efficiency and data-driven insights.