Ankit Punjabi
About
Detail
Data Scientist at Pratt Street Capital
Jersey City, New Jersey, United States
Résumé
Jobs
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- SStealth startup - Founding engOct 2025 - Nov 2025 (2 months)
- PData ScientistPratt Street CapitalAug 2025 - Current (10 months)As a Data Scientist, I was responsible for designing and implementing advanced data models and algorithms to extract insights from complex datasets. My role involved extensive data analysis and the application of statistical methods to inform business decisions, leveraging tools such as Python, TensorFlow, and PyTorch. I developed and maintained data pipelines using Airflow and Kubeflow, ensuring efficient data flow and processing across various platforms, including Microsoft Azure and Google Cloud Platform (GCP). Additionally, I utilized my knowledge of MLOps to streamline machine learning workflows and enhance model deployment. While Microsoft Excel was not a primary tool in my data science toolkit, I effectively engaged with stakeholders
Graduate Teaching AssistantRochester Institute of TechnologyJan 2025 - May 2025 (5 months)As a Graduate Teaching Assistant, I supported the course ISTE-608 Database Design and Implementation under Prof. Charles Border, as well as the Foundations of Data Science and Analytics with Prof. Ezgi Siir Kibris. My responsibilities included assisting in the development of course materials, facilitating discussions, and providing guidance to students on complex topics such as database design, SQL, and data structures. Additionally, I leveraged my knowledge of Python and NoSQL to enhance the learning experience. I developed and deployed an agentic AI framework to streamline the grading process for coding-based assignments, which improved efficiency and provided students with timely feedback. This innovative approach not only showcased my s- ML - InternAllsoft Solutions and services Private LimitedFeb 2023 - Apr 2023 (3 months)As an ML Intern, I contributed to the development and implementation of machine learning models, including a facial recognition system, while actively participating in sprint reviews to ensure alignment with core software development life cycle (SDLC) principles. My role involved conducting thorough data analysis and cost assessments for stakeholders, which included evaluating expenses related to cloud infrastructure. Additionally, I utilized Tableau to present comparative insights, enhancing the decision-making process regarding resource allocation. This experience allowed me to apply my skills in data engineering and MLOps, while also gaining exposure to business analysis, ensuring that our projects met both technical and business objecti
Education
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- Master's degree, Data ScienceRochester Institute of TechnologyJan 2023 - Dec 2025 (3 years)
- Bachelor of Technology - BTech, Artificial IntelligenceShri Vaishnav Vidyapeeth Vishwavidyalaya IndoreJan 2019 - Dec 2023 (5 years)
Projects (professional or personal)
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- AAI Job Scam DetectorJul 2025 - Aug 2025 (2 months)As an AI Job Scam Detector, I was responsible for developing and implementing advanced algorithms to identify fraudulent job postings, leveraging my expertise in data analysis and natural language processing (NLP). I utilized Python, along with libraries such as Pandas and NumPy, to manipulate and analyze large datasets effectively. My role involved creating robust data pipelines to ensure seamless data flow and integration, while also employing machine learning (ML) techniques to enhance detection accuracy. Additionally, I worked with NoSQL databases to manage unstructured data, although I also had experience with SQL, which was used for storing and querying structured data within the project. My proficiency in Git facilitated efficient ve
- EElection-Driven Stock Market Volitality Forecasting with BERT | CapstoneAug 2024 - Current (1 year 10 months)As part of my capstone project titled "Election-Driven Stock Market Volatility Forecasting with BERT," I led a team of three over two semesters, utilizing a two-week sprint methodology to conduct extensive machine learning research and develop predictive models. This project involved leveraging advanced techniques in natural language processing (NLP) and artificial intelligence (AI) to analyze sentiment and its impact on stock market volatility. While the primary focus was on utilizing BERT for sentiment analysis, I also integrated data visualization tools such as Microsoft Power BI and Tableau to present our findings effectively. Additionally, I applied my knowledge of the software development life cycle (SDLC) to ensure a structured appro
- IImproving what LLMs Predict for CodingFeb 2024 - Aug 2024 (7 months)In the role of Improving what LLMs Predict for Coding, I focused on enhancing the predictive capabilities of large language models (LLMs) specifically for coding applications. My responsibilities included conducting thorough data analysis and utilizing advanced coding techniques to refine model outputs. I employed Python, along with libraries such as Pandas and NumPy, to manipulate and analyze data effectively. Additionally, I leveraged Git for version control and collaborated on projects using TensorFlow and PyTorch to implement machine learning algorithms. To support the development of robust data pipelines, I integrated data engineering practices, ensuring seamless data flow and processing. Furthermore, I utilized data scraping technique
- 11000 Cameras - Value for money Statistical AnalysisAug 2023 - Dec 2023 (5 months)
- RRAGenius | AI Driven Document ChatBotAs a RAGenius | AI Driven Document ChatBot specialist, I was responsible for developing and optimizing chatbot functionalities that enhance document management processes. My role involved leveraging advanced natural language processing (NLP) techniques to ensure seamless interactions between users and the chatbot. I utilized Python and various libraries such as Pandas and NumPy for data manipulation and analysis, while also implementing data pipelines to streamline data flow. Additionally, I employed Kubernetes for container orchestration, ensuring efficient deployment and scalability of the chatbot services. Although SQL was identified as a non-relevant skill, I effectively utilized PGvector, a vector database that operates on PostgreSQL,