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Muhammad Usman A. AI, Cloud and Data Analytics Platforms

My name is Muhammad Usman A. and I have over 19 years of experience in the tech industry. I specialize in the following technologies: Looker Studio, Tableau, Microsoft Power BI, SQL, Data Visualization, etc.. I hold a degree in Bachelor of Computer Science (BCompSc), . Some of the notable projects I’ve worked on include: HR Dashboards & Performance Management System, Knime ETL / Advanced Data Engineering, Real Estate Sales Analysis, PowerBI Project, Comparable Home Finder Valuation, etc.. I am based in Lahore, Pakistan. I've successfully completed 22 projects while developing at Softaims.

I am a dedicated innovator who constantly explores and integrates emerging technologies to give projects a competitive edge. I possess a forward-thinking mindset, always evaluating new tools and methodologies to optimize development workflows and enhance application capabilities. Staying ahead of the curve is my default setting.

At Softaims, I apply this innovative spirit to solve legacy system challenges and build greenfield solutions that define new industry standards. My commitment is to deliver cutting-edge solutions that are both reliable and groundbreaking.

My professional drive is fueled by a desire to automate, optimize, and create highly efficient processes. I thrive in dynamic environments where my ability to quickly master and deploy new skills directly impacts project delivery and client satisfaction.

Main technologies

  • AI, Cloud and Data Analytics Platforms

    19 years

  • Looker Studio

    9 Years

  • Tableau

    15 Years

  • Microsoft Power BI

    5 Years

Additional skills

  • Looker Studio
  • Tableau
  • Microsoft Power BI
  • SQL
  • Data Visualization
  • LLM Prompt Engineering
  • SaaS
  • ETL
  • Data Analytics
  • Snowflake
  • AI Product Management
  • Electronic Medical Record
  • KPI Metric Development
  • Microsoft SQL Server
  • Data Analytics & Visualization Software
  • Data Engineering
  • Data Science
  • Data Analysis

Direct hire

Potentially possible

Previous Company

CureMD

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Experience Highlights

HR Dashboards & Performance Management System

KPIs for HR departments: Headcount Metrics: Number of employees, new hires, terminations. Turnover Rate: Percentage of employees leaving. Retention Rate: Percentage staying. Time to Hire: Average time to fill positions. Cost per Hire: Hiring expenses. Employee Satisfaction: Survey scores. Diversity Metrics: Gender, race, ethnicity distribution. Employee Performance: Evaluation scores. Absenteeism Rate: Workdays missed. Training Hours: Training per employee.

Knime ETL / Advanced Data Engineering

Project was to have complex data integration with lot of transformations and we used Knime Analytics platform.

Real Estate Sales Analysis

The "Real Estate Sales Analysis" project encompasses a comprehensive examination of property sales data within a specific market or region. Utilizing statistical methods and data analytics, this initiative aims to dissect and interpret trends, patterns, and fluctuations in real estate sales. By analyzing factors such as property types, sale prices, market trends, and seasonal variations, the project aims to provide insights beneficial for real estate professionals, investors, and stakeholders. The goal is to deliver a comprehensive overview that aids in understanding market dynamics, identifying opportunities, and making informed decisions within the real estate sector.

PowerBI Project

PowerBI project for HR department of a large retailer KPIs for HR departments: Headcount Metrics: Number of employees, new hires, terminations. Turnover Rate: Percentage of employees leaving. Retention Rate: Percentage staying. Time to Hire: Average time to fill positions. Cost per Hire: Hiring expenses. Employee Satisfaction: Survey scores. Diversity Metrics: Gender, race, ethnicity distribution. Employee Performance: Evaluation scores. Absenteeism Rate: Workdays missed. Training Hours: Training per employee.

Comparable Home Finder Valuation

This project focuses on leveraging data analytics to determine accurate property valuations by identifying and analyzing comparable homes in a specific market. By utilizing real estate data and applying valuation models, this initiative aims to identify similar properties based on various criteria such as location, size, amenities, and recent sales. The project employs statistical analysis to assess market trends, property features, and neighborhood attributes to derive fair and competitive valuations for residential properties.

Education

  • University of Engineering & Technology, Lahore

    Bachelor of Computer Science (BCompSc) in Data Science & Analytics

    2009-01-01-2013-01-01

  • HARVARD BUSINESS SCHOOL EXECUTIVE EDUCATION

    in

Languages

  • English