beBee background
Technology / Internet
dauda faruq

dauda faruq

Data Scientist, Machine Learning Engineer.
Ikeja, Ikeja


About dauda faruq:

Experienced data scientist with a strong background in predictive modeling, data cleaning, and machine learning. Proficient in Python programming, time series forecasting, AI model development, and deep learning. Passionate about using data-driven insights to solve complex problems. Seeking opportunities to contribute expertise to innovative data science projects


● AttainBase, AI Software Developer, Apr 2023 - Present - 

Finetuned the TAPAS model on a custom dataset prepared from the company's database, enhancing information retrieval and analysis. - Developed data preprocessing pipelines to clean and transform raw data into usable formats for training and inference. - Collaborated with cross-functional teams to integrate AI-powered features into the company's products. - Conducted experiments and A/B tests to optimize model performance and fine-tune hyperparameters. 

● Zummit Infolabs, Junior Data Scientist, Nov 2021 - Present 

Built AI models for breast cancer classification and prediction using Knn, decision trees, random forest, and logistic regression algorithms. 

Built multiple ML models from the same datasets for algorithm and accuracy comparison. 

Built a spam mail classification model. 

Completed daily programming tasks assigned to me.  

Worked on a satellite imagery detection project. 


●, Junior Data Scientist, Sep 2021 - Nov 2021  

Collaborated with data scientists to build and deploy predictive machine-learning models for car prices. 

Completed personal coding tasks. 


● ANZ Financial, Data Scientist, Oct 2020 - Feb 2021

Collaborated with senior data scientists to clean data for machine learning modeling. Evaluated machine learning models for performance testing. 


● Breast Cancer Prediction Model: Used datasets collected from a hospital in Wisconsin on Kaggle to build a classification model to predict benign and malignant cancer. The model was developed as a basic web app and used Knn, decision trees, random forest, and logistic regression algorithms. 

● Electric Car Price Prediction Model: Built a model with 80% accuracy on predicting the prices of different electric cars using a car price dataset scraped from different web sources. 

● Spam Mail Classification Model: Built an ML model that predicts whether an email is spam or not using algorithms that convert words to floats before training the model. ●Face Detector: Trained a convolutional neural network model on my own image dataset to classify my picture as class 1 and not my pictures as class 0. 

● Satellite Imagery Detection: Built a model to detect features and classify objects from satellite images.


University of PortHarcourt, Rivers State, Nigeria

Biomedical Technology, 2016.

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