Divyanshu Srivastava
ML EngineerAI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Data Scientist | AI | ML | LLM | Research
I am a B.Tech (Hons.) graduate in Computer Science from IIIT Ranchi, with a strong foundation in machine learning, deep learning, and data science. My expertise includes building predictive models, developing APIs, and creating data-driven dashboards to optimize business processes. I have hands-on experience with Python, C++, TensorFlow, and PyTorch, and have successfully worked on projects ranging from fraud detection to image classification. Being a CS graduate has shaped my ability to approach real-world problems with a futuristic mindset, and I am particularly interested in emerging technologies like Quantum Computing. I am a fast learner, adaptive, and possess strong leadership skills, allowing me to manage teams efficiently and contribute meaningfully to innovative solutions in AI, machine learning, and data science.
Indian Institute of Information Technology Ranchi
Bachelor's degree, Computer Science
January 1, 2017 – January 1, 2021
Orinson Technologies Private Limited
Machine Learning Intern
December 1, 2024 – January 1, 2025
Lucknow, Uttar Pradesh, India · Remote
Dream Tech Training and Research Centre
Data Scientist
July 1, 2023 – June 1, 2024
Lucknow, Uttar Pradesh, India · On-site
Indian Institute of Technology (Banaras Hindu University), Varanasi
Technical Specialist Intern
May 1, 2019 – July 1, 2019
Varanasi, Uttar Pradesh, India
Smart India Hackathon
Machine Learning Specialist
March 1, 2019 – March 1, 2019
Bhubaneshwar, Odisha, India
OSA Student Chapter @IIITR
Technical Secretary
August 1, 2018 – July 1, 2021
Ranchi, Jharkhand, India
Boston-House-Pricing Web Application
October 1, 2022 – December 1, 2022
Created a Machine Learning model using Multiple Regression on the Boston Housing Dataset. Developed an API using Flask and deployed a web application on Heroku, improving prediction accuracy by 15%.
Malaria Detection System
June 1, 2022 – September 1, 2022
Formulated a Deep Learning model with VGG-19 and VGG-16 for malaria cell detection, achieving 92% accuracy. Executed the application on Heroku using Flask, streamlining image analysis.
SMS-Spam Classification Application
November 1, 2020 – January 1, 2021
Adopted a classic machine learning method for building the classifier. • Used TF-IDF vectorization to vectorize the words. • Experimented with various classification algorithms, with Extra-Trees Random Forest Classifier producing the best results. • Used accuracy score and precision score as metrics due to high dataset imbalance. • Developed a machine learning-based application using Flask to predict and detect SMS spam messages. • Deployed the application on the Heroku Cloud Platform.
Flower Classification System using PyTorch Framework
August 1, 2020 – October 1, 2020
• Developed a deep learning model using two methods: ResNet CNN on the Flower Recognition Dataset from Kaggle, and Transfer Learning on a pre-trained ResNet-34 CNN on the same dataset. • Performed the analysis using the PyTorch open-source framework.
Higgs Boson Challenge
June 1, 2020 – June 1, 2020
I used the classical feature engineering approach as well as deep learning using H2O and tried to analyze the data by their graphs, scatter plots, histograms, and probability distributions using dataset generated by ATLAS at CERN(European Organization for Nuclear Research) in 2012. I have also learned using convolutional neural network to the voxelized 3D and projected 2D images of charged particle trajectory recorded in liquid argon bubble chamber using Larcv, Tensorflow, Numpy, Pandas profiling libraries from DeepLearningPhysics community and solve single-particle systems in particle physics, 2019.
Design and Optimization of Performance Parameters of Indirect Solar Dryer System
May 1, 2019 – July 1, 2019
Designing of Solar Dryer is done and its performance parameters are optimised using Genetic Algorithm under Dr. S.K. Shukla at IIT Varanasi, 2019.
Income Tax Fraud Detection
March 1, 2018 – March 1, 2018
Artificial Neural Networks and Machine Learning at Smart India Hackathon under the banner of FIS Solutions. Team name- Tachyonss at C.V. Raman College of Engineering, Bhubaneswar, 2019.
Machine Learning
CETPA Infotech Pvt. ltd.
June 25, 2026 – Present
What Is Generative AI?
June 25, 2026 – Present
Streamlining Your Work with Microsoft Copilot
June 25, 2026 – Present
Generative AI: The Evolution of Thoughtful Online Search
June 25, 2026 – Present
From the Big Bang to Dark Energy
The University of Tokyo
June 25, 2026 – Present
Introduction to Programming Using Python
CETPA Infotech Pvt. ltd.
June 25, 2026 – Present
Introduction to Career Skills in Data Analytics
June 25, 2026 – Present
Cultural Fit Analysis
The candidate's project history shows a strong focus on personal projects and hackathons, indicating initiative and a passion for machine learning. However, the professional experience is limited to internships and a single full-time role as a Data Scientist. While the projects align well with an ML Engineer role, the breadth of experience in a corporate setting and exposure to diverse team structures is not extensively detailed. The certifications are mostly introductory or general, not deeply specialized for a senior ML Engineer role, which might suggest a need for more focused professional development. The candidate's experience is primarily in model development and deployment, which fits the target role, but the depth of experience in large-scale, production-grade ML systems is not clearly evident.
Soft Skills & Operational Fit
The candidate's project descriptions indicate an ability to work on diverse problems and deploy solutions, suggesting a results-oriented approach. Experience as a 'Technical Secretary' and 'Machine Learning Specialist' in a hackathon implies some level of teamwork and communication, though specific soft skill demonstrations are limited in the provided data. The 'Technical Specialist Intern' role involved optimizing systems, indicating problem-solving and analytical skills.