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Gagandeep, Gen AI Scientist at Property Software Company: Advize Career Interview
Gagandeep's journey from a Data Scientist role at Conduent, leveraging predictive modeling and customer segmentation, to a Gen AI Scientist at a property software company showcases a dynamic career path.
The interview reveals a multifaceted role architecting multi-agent systems, fine-tuning generative AI models, and leading a data science team.
A Master's in Business Analytics and experiences at Walmart Labs and other companies contributed to expertise in large language models and AI-driven automation.
Success in this field requires a blend of technical skills (Python programming, cloud platforms, and Gen AI model pipelines), leadership abilities, and adaptability to the rapidly evolving AI landscape.
The most impactful experience involved a research assistant role applying data science to real-world problems, accelerating career progression.
This inspiring trajectory highlights the importance of continuous learning, domain knowledge, ethical considerations, and effective communication in achieving success as a Gen AI Scientist.
A strong foundation in data science, proactive pursuit of experience, and strategic networking were key factors contributing to Gagandeep's achievements.
Advizer Information
Name
Job Title
Company
Undergrad
Grad Programs
Majors
Industries
Job Functions
Traits
Gagandeep Singh
Gen AI Scientist
Property Software Company
Uttar Pradesh Technical University
Arizona State University (ASU) - W. P. Carey
Computer Science
Technology
Data and Analytics
None Applicable
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Career Path of a Generative AI Scientist at a Property Tech Company
Gagandeep's career progressed from a Data Scientist role at Conduent, focusing on "predicting enrollments, customer segmentation," to a Lead Data Scientist at Tata Consultancy Services, where they worked with unstructured data and NLP. A Master's in Business Analytics and subsequent roles at Walmart Labs and a real estate property management company saw their expertise evolve to encompass large language models and "automating staff" using AI for tasks such as call summarization and email systems.
Main Responsibilities of a Gen AI Scientist at RealPage
Gagandeep's role as a Gen AI Scientist at a property software company is multifaceted, encompassing "architecting multi-agent systems," developing and fine-tuning generative AI models using techniques like low-rank adaptations, and leading a data science team while establishing ML Ops practices. This dynamic position, which includes spearheading projects like "call summarization, video chatbots, and AI email systems," also involves continuous learning and knowledge sharing, reflecting a commitment to both scientific advancement and team mentorship.
A Day in the Life of a Gen AI Scientist at Property Software Company
A typical day for a Gen AI Scientist data science manager is "quite varied," involving a mix of hands-on work like "coding or model optimization" and leadership tasks such as team check-ins, project strategy meetings, and collaboration with product teams. This is complemented by continuous learning through research papers and online courses to stay abreast of advancements in the field.
Most Important Skills for a Generative AI Scientist at Property Software Company
Gagandeep, a Gen AI Scientist, highlights the crucial technical skills for success in their field: "proficiency in gen AI model pipelines and large language models, fine tuning," strong programming skills (especially Python), and knowledge of cloud platforms like AWS and Azure. Beyond technical expertise, leadership and team management are also essential, reflecting the senior level of the role and its responsibilities.
Favorite Parts Of Being A Gen AI Scientist At A Property Software Company
Gagandeep, a Gen AI Scientist, thrives on the "cutting edge technologies" and daily challenges inherent in their role, constantly learning and applying advancements in the field to improve both client experience and internal team learning within the Property Software Company. Their extensive NLP experience proves invaluable in navigating this "exciting era" of AI.
Biggest Challenges for a Gen AI Scientist at a Property Software Company
Gagandeep's greatest challenge as a Gen AI Scientist involves the "rapid pace of change in AI," requiring constant learning and adaptation, as seen in their recent transition to large language models like GPT 3.5. This is further complicated by managing stakeholder expectations, addressing AI limitations and risks like bias, and maintaining team motivation and productivity amidst rapid technological advancements.
Favorite Parts Of Working In The AI Industry As A Generative AI Scientist
Gagandeep, a Gen AI Scientist, finds the "transformative potential" of the tech industry most rewarding, particularly the ability to "revolutionize industries and improve people's lives," as seen in their work developing AI systems for more efficient property management. The collaborative nature of the field and its constant evolution, with "new breakthroughs" continually emerging, also provide significant intellectual stimulation.
What Type Of Person Thrives In Artificial Intelligence, According To A Gen AI Scientist At Property Software Company
Success in the Gen AI industry requires a "unique blend of technical prowess and software skills," including strong math, statistics, and programming foundations, coupled with intense curiosity and adaptability to the rapidly evolving field. The ability to translate "theoretical concepts into practical solutions" and communicate effectively with both technical and non-technical stakeholders is also crucial for career advancement.
What a Gen AI Scientist at Property Software Company Wishes They Had Known Before Entering the AI Industry
Gagandeep, a Gen AI Scientist, wishes they had known the crucial role of "domain knowledge" and the "iterative nature of AI development," highlighting the real-world challenges of data preparation and model refinement beyond textbook examples. The ethical implications of AI, building models that are "fair, transparent, and beneficial to society," are also key learnings from their experience.
Entry-level Positions for Aspiring Generative AI Scientists at Property Software Company
Entry-level AI/data science roles for undergraduates include "junior data analyst or junior data scientist," machine learning engineer, research assistant, and business intelligence analyst positions; Gagandeep also stresses the importance of internships and building a portfolio through open source contributions or data science competitions to gain "hands-on experience" and solve "actual business problems."
Significant Career Lesson From A Generative AI Scientist At A Property Software Company
Gagandeep's career highlights the crucial need for "adaptability and continuous learning" in the rapidly evolving AI field, a lesson learned through transitions from traditional ML techniques to deep learning and a shift from individual contributor to data science manager. This journey also underscored the importance of combining "technical expertise with leadership and communication skills," and the ethical considerations vital in AI development.
College Experiences That Helped a Gen AI Scientist at Property Software Company Succeed
Gagandeep's undergraduate coursework in information technology, including early exposure to neural networks and foundational data science concepts, provided a strong base for their career in Gen AI. Further, their proactive pursuit of real-world application through internships and research, coupled with focused development of communication skills via presentations and competitions, proved instrumental in bridging the gap between theory and practice and building a strong foundation for career success.
How Identity Influenced a Gen AI Scientist's Career at Property Software Company
Gagandeep's most impactful experience at WP Carey was their research assistant role at the Actionable Analytics Lab, "a game changer both academically and professionally," providing invaluable real-world experience applying data science to projects for a major company like Aidas, ultimately accelerating their technical skills and securing a position at Walmart post-graduation. This experience, including developing a "multi-label text classification model," solidified their career trajectory in AI.
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