Data Engineer

646-***-**** Haseeb haseeb.asim@Asim columbia.edu haseebasim

Education Master of Science in Applied Analytics – Columbia University in the city of New York April 2021 Courses: Analytics - Frameworks & Methods I/II, Research Design, Storytelling with data (Data Visualization), Analytics in Organizational Context, Bachelor Managing of Science Data, Strategy in Computer & Analytics, Science Machine – Lahore Learning University in Finance, Natural of Management Language Processing, Sciences Digital Product Innovation Jun 2018 Graduated with Distinction, Dean’s Honor List 4 consecutive years (GPA: 3.70) Courses: Statistics & Data Analysis, Data Structures, Data mining, Artificial Intelligence, Advanced Programming, Network Security Skills

• Advanced experience in data analysis in Excel including creating macros in VBA and dashboards using Pivot tables

• Practical experience in Project Management software including Microsoft Project for task scheduling and resource allocation

• Proficiency in programming languages including Python, SQL, C/C++, Matlab, Node, Javascript, GO, Haskell, MongoDB, Cassandra

• Experience in data analysis and regression using STATA, R

• Comprehensive knowledge of Big data technologies including Hadoop, Pig, Hive, Spark, Flume, Sqoop, Kafka Work Data Science Experience Capstone – Philips (New York) Sep 2020 – Dec 2020 As part of Columbia Applied Analytics Program: Solving Real World Problems with Analytics

(In keeping with a confidentiality agreement signed with the company, specifics of the project and their data cannot be disclosed)

• Analyzed current demand forecasting approaches used within the company with the goal of improving predictions.

• Created and experimented with Machine Learning models including Gradient Boosting, Random Forest, Linear Regression and Linear Mixed Effects Regression.

• Presented and reported our findings to senior executives within the company, compared the new models to their Financial current Engineer implementation, Intern – Recursion identified Co. areas (New that York) posed problems and suggested processes for further Jun 2020 improvement. – Dec 2020

• Created automated monthly financial reports curated as per client specifications across various domains.

• Created interactable dashboards to visualize current mortgage markets (in R Shiny) and provide actionable insights.

• Created automated programs to scrap and parse large sets of real estate and tax data from state county websites Software using Engineer Selenium, Intern Beautiful – Earth Soup Institute, and Scrapy. Columbia University (New York) Jun 2020 – Sep 2020

• Developed a web app to gather data from rural areas incorporating principles of gamification in order to facilitate the creation of a better index insurance for farmers (using Flask in Python)

• Developed a text-based surveying platform (SMS/WhatsApp) to provide an alternate data collection platform for farmers without smartphones/internet connections using Twilio API implemented in Python.

• Integrated the new system’s database into their existing database (PostgreSQL). COO - DCON Construction (Pakistan) Jun 2018 – Dec 2019

• Streamlined project scheduling, procurement and resource management for 10-15 concurrent projects across multiple cities with timelines ranging from 2 months to 1 year.

• Allocated funds, established billing cycles and managed cash flows with revenues of 300 million+ PKR annually.

• Led negotiations with all high-volume vendors on material unit rates and credit terms ensuring all material was delivered to construction site as per schedule and the company’s credibility with market vendors was maintained.

• Created an inventory management system for frequently used construction material in order to ensure accountability for all items sent to construction site.

• Oversaw the tendering department in charge of bidding for new projects and introduced a mechanism to record material and labor costs for ongoing projects to make future tendering more accurate. This process not only enabled the company to reduce project cost but also increase profitability.

• Developed a payment recovery mechanism to ensure all pending issues on construction sites were resolved and all final bills were processed. This helped minimize the huge gap between payables and receivables.

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