Hello!

I'm Mohammed Sohaib Uddin



A data-driven problem solver.

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Name: Mohammed Sohaib Uddin

Experience: 6+ Years

Address: Chicago, USA

Skills

SQL 95%
Python 85%
Power BI 85%
Data Analysis 90%
Machine Learning 85%
Deep Learning 85%
PySpark 80%
Big Data 80%

About

About Me

Seasoned Data Scientist with over 6 years of extensive expertise in Data Analysis, Power BI, Python, SQL, Machine Learning, Deep Learning, and Big Data. Skilled in a wide array of models including Linear Regression, Logistic Regression, Decision Trees, Random Forest, SVM, K-Nearest Neighbors, Bayesian, CNN, RNN, LSTM, NLP, and more. Masters in Collaborating with cross-functional teams to deliver high-quality solutions, saving project costs.

  • Technologies: Machine Learning, Deep Learning, Big Data, Business Intelligence, Batch and Streaming Processing
  • Domain: Retail, Ecommerce, Food Delivery & Digital Marketing
  • Tools: Power BI, Tableau, Databricks, Data Factory, Apache Spark, Hive
  • Programming: Python, R, Scala, SQL (MySQL, Spark-SQL)
  • Frameworks and Libraries: Django, Flask, NumPy, Pandas, Scikit-Learn, Matplotlib, TensorFlow, PySpark, Hadoop, Kafka
  • Machine Learning Algorithms: Random Forest (RF), Decision Trees (DT), Linear Regression (LR), Support Vector Machines (SVM), K-Nearest Neighbors (KNN), Naive Bayes, Neural Networks
  • Deep Learning Architectures: Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN), Long Short-Term Memory (LSTM)
  • NLP Techniques: Sentiment Analysis, Named Entity Recognition (NER), Topic Modeling, Word Embeddings
  • Other Skills: Azure Cloud, HDFS, Agile, Excel, Git, JIRA, Google Analytics & SEO

0 +   Projects completed

LinkedIn

Resume

Resume

Seasoned Data Scientist with 6+ years of experience driving business strategies through data-driven insights. Proven expertise in business intelligence, data science, big data, statistical analysis, machine learning algorithms and project management.

Experience


Oct 2022 - Present

Data Science Research Assistant

Northern Illinois University

NIU, situated in DeKalb, Illinois, is a public research university established in 1895.

  • Utilized CNN with pre-trained models on satellite imagery for lung cancer detection, enhancing treatment strategies. Also developed image segmentation, classification, and feature extraction models.
  • Led 25 volunteers to collect a precise satellite dataset of 10,634 locations, reaching 94% labeling accuracy.
  • Built predictive models for Illinois’s solid waste management, achieving 97.5% accuracy in impact analysis.

Aug 2023 - Dec 2023

Graduate Analytics Consultant - ELC

Silverthorne Homebuilders

Silverthorne is homebuilding company offering customizable homes and dedicated service in Chicagoland and Eastern Iowa.

  • Conducted predictive analytics on financial, customer, and market data for Silverthorne's expansion strategy.
  • Led GIS-driven campaigns, increasing email open rates by 25% and boosting customer engagement by 15%.
  • Orchestrated cross-functional team efforts, driving strategies for 28% lead generation and 18% ROI growth.

Mar 2019 - Jul 2022

Data Scientist

Pianalytix

Pianalytix empowers businesses with AI-driven process optimization, efficiency, and profitability..

  • Led the design and implementation of a Data pipeline for clients, reducing data processing time by 25%.
  • Migrated On premise Data Distribution to Azure Cloud Distribution and Hive Data Warehouse using Pyspark.
  • Achieved proficiency in Azure Data Factory, Databricks, ADLS Gen2, Delta Lake and other Azure services.
  • Engineered CNN-powered image recognition for automated product categorization, reducing manual errors by 20%.
  • Developed predictive models for dynamic pricing, achieving a 16% increase in sales using Python and SQL.
  • Designed image-based product search, enabling users to find items using images with a 30% efficiency increase.
  • Applied sentiment analysis on customer reviews in a food delivery app, to identify trends for restaurant partnerships.
  • Utilized agile scrum methods, collaborating with cross-functional teams to deploy ML models in production, reducing manual processes, enhancing efficiency.

Aug 2018 - Mar 2019

Data Assosicate

Amazon

Amazon is a multinational technology company focusing on e-commerce, cloud computing, digital streaming, and artificial intelligence.

  • Enhanced listing data accuracy, minimizing database discrepancies significantly for over 200 sellers.
  • Partnered with sellers to deploy data-driven marketing campaigns, leading to a 25% surge in engagement metrics.
  • Executed seller-tailored data analytics for inventory management, reducing stockouts and optimizing levels.
  • Analyzed sales and product trend data to identify upselling prospects, driving sales growth for participating sellers.

Jun 2016 - Jul 2018

Data Analyst

Sufa Digital Media

At Sufa Digital, they combine creativity, data science, and AI to assist businesses in thriving within the digital era with unprecedented success.

  • Built queries to merge data sources, creating dynamic product sales dashboards in Tableau.
  • Analyzed CRM data using Python & Tableau, delivering detailed monthly insights on product quality and sales metrics.
  • Combined sales and forecast data to estimate product lifetime values, comparing with previous generations.
  • Engaged in stakeholder meetings for business needs, aligning solutions with end-user needs through collaboration.



Education


2022 - 2024

Master of Science in Management Information Systems

Northern Illinois University

Grade: 3.8

2015 - 2018

Bachelor of Engineering in Mechanical Engineering

Osmania University

Grade: First class distinction.

2012 - 2015

Diploma in Mechanical Engineering

Government Polytechnic College

Grade: First class distinction.

Download CV

Projects

Projects

Below are a few projects in Data Science, Data Engineering, and Python.

Heart Disease Prediction Using Machine Learning

Engineered ML model for heart disease prediction using curated patient attributes, aiming at accurate disease identification.

Flask App for Plant Disease Prediction Using Deep Learning

Flask-based application leveraging Deep Learning for accurate prediction of plant diseases.

Traffic Sign Classification Using LeNet Network in Keras

Traffic sign classification using Le-Net architecture in Keras for 43 different classes.


Forecasting Walmart Store Sales

Sales forecasting for Walmart stores based on historical data and promotional markdown events.

More projects on Github

I love to solve problems & uncover hidden data stories


GitHub

Contact

Contact Me

Below are the details to reach out to me!

Address

Chicago, IL, USA

Contact Number

+1 779-775-3979

Email Address

sohaibdataengineer@gmail.com

Download Resume

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