Profile
I’m Abhishek Teni, a data scientist and web developer with an MSc in Data Science and Analytics. Currently a Generative AI Annotator at Meta in Dublin, I excel in both frontend and backend technologies and am passionate about solving technical challenges and learning new skills.
Education
Msc Data Science and Analytics
Maynooth University Grade: 73% (1:1) 2022-2023B.E Computer Science
Smt. Kashibai Navale College of engineering, Pune 2017-2021 Grade: 78% (1:1)Interests
Experience
Generative AI Annotator(Current position)
June 2024 |Covalen SolutionsData Annotation and Labeling for Meta’s AI model: Conduct detailed annotations and labeling of data to train and enhance the generative AI model. Annotated over 100,000 data points with 85% accuracy, ensuring high-quality input for model training.
Full stack Developer & Team lead
February -June 2024 |Sciliamialed a team of 4 MERN stack developers in designing, developing, and maintaining full-stack web applications. Design and develop scalable and maintainable architectures for web applications using the MERN (MongoDB, Express.js, React.js, Node.js, Redux, Material UI, WordPress) stack. Implement responsive and intuitive user interfaces utilizing React.js and other modern front-end frameworks
MERN stack Developer
January - April 2022 |XcitEducation WorldwideAfter Engineering, I contributed in various consistent MERN STACK DEVELOPMENT projects that I undertook in various segments in majorly contributing to the open-source community, for students coming from poorest section in general.
Data Analyst
2020 |NKM PLANNING SOLUTIONDuring Engineering, I interned in N.K.M Planning solution, under the guidance of Mr. Kedar Shelker, founder where I Assisted senior data analyst in the collecting and figuring different construction analytics of various domain and sector
Projects
OrderSwift: Hotel Order Management System
Developed a full-stack hotel order management application using Next.js, Supabase, and Tailwind CSS, hosted on Vercel. The app enhances order processing efficiency and communication between front-end and kitchen staff, following MVC architecture and implementing secure user authentication.
Conference Management
Developed a full-stack CRUD application using React, Node.js, and MongoDB with Material UI, featuring role-based dashboards for Admins, Authors, and Reviewers. The app facilitates paper submission, review, and feedback, ensuring data integrity with JWT, bcrypt, and validator libraries.
Deep Ensemble learning model for analyzing the wholesale price and energy demand in a particular domain(LSTM)
Developed a deep ensemble model using Stack LSTM and customized LSTM in Python to predict electricity prices and mitigate market irregularities. The solution employs data-driven techniques for accurate forecasting, enhancing decision-making for stakeholders.
A Decentralized application for Document Storage and Verification
A Platform which serves as a solution for safe storage of the documents and quick verification of the documents using Blockchain technology
Skills
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HTML/CSS
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Javascript,typescript
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React.js, next.js
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Mongo DB & Postgresql
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Python/R
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Jest & cypress