Pranav Gupta

Data Analyst

Akola, Maharashtra 0+ yrs exp 81 · Excellent

About

Highly motivated Data Science and AI professional with a strong academic foundation in Physics, Chemistry, and Mathematics (B.Sc.). Completed a Data Science and AI Diploma from the reputed institute DataMites, gaining hands-on experience in machine learning, deep learning, and natural language processing (NLP). Successfully completed an Internship as a Data Science Intern at Rubixe AI Solutions, where I worked on real-world datasets, built predictive and analytical models, and contributed to business-driven AI solutions. Passionate about applying data-driven techniques to solve complex problems and deliver impactful insights.

Skills & Expertise (57)

Python Intermediate

7.5/10

0.5

Years Exp

Teamwork Intermediate

7.0/10

0.5

Years Exp

Pandas Intermediate

7.0/10

0.5

Years Exp

Effective Communication Intermediate

7.0/10

0.5

Years Exp

Deep Learning Intermediate

6.5/10

0.5

Years Exp

scikit-learn Intermediate

6.5/10

0.5

Years Exp

SQL Intermediate

6.5/10

0.5

Years Exp

TensorFlow Intermediate

6.0/10

0.5

Years Exp

Natural Language Processing Intermediate

6.0/10

0.5

Years Exp

Git Intermediate

6.0/10

0.5

Years Exp

Docker Adaptability GitHub Kubernetes Time management Streamlit FastAPI Seaborn Matplotlib Critical thinking Problem Solving Transfer Learning OCR Face Recognition Image Processing Logging Environment Configuration Secure File Handling REST API development JWT Authentication Password hashing SQLite Decision Tree Statistical Analysis NumPy PyTorch SpaCy NLTK MySql MongoDb Linear Regression Logistic Regression Clustering SVM KNN Tableau Random Forest XGBoost ANN CNN RNN LSTM GRU Applied statistics Transformers Excel Power BI

Work Experience

Data Science Consultant

Rubixe AI Solutions

Aug 2025 - Jan 2026

Collaborated with the team members to understand client requirements and business challenges. Worked on a client project where machine learning algorithms like decision tree, XGBoost, and random forest algorithms were applied and achieved 95% test accuracy. Played a key role in the project team and ensured the timely submission of the projects. Constructed predictive models using machine learning algorithms (Random Forest), achieving an accuracy rate of 85% in attributing revenue and conversions to specific marketing touchpoints.