Summary
Overview
Work History
Education
Skills
Timeline
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Ausaf QS

Macquarie Park,NSW

Summary

An absolute data nut with around 4 years of experience working as a Data Scientist adopting Agile methodologies, building end to end data science products from ground in a small team with wide variety of responsibilities, from extracting insights to data engineering and deploying ML models on cloud

Overview

4
4
years of professional experience

Work History

Senior Data Engineer

VentureCrowd
01.2023 - Current
  • Increased Average Click through Rate for Email Marketing from 1.1% to 2.5 % by creating data segregation for targeted marketing
  • Boosted lead Generation by 200 % using ML models to predict investors investment behavior
  • Facilitated and led data workshops aimed at engaging employees, fostering a culture of data literacy, and steering the organization towards a more data-driven approach
  • Predicting investor investment amount to divert more resources towards high investment opportunities which brought in at least 1,000,000 dollars in investment in 2023
  • Designed and implemented a Tableau dashboard to monitor investment targets, enabling strategic prioritization and informed decision-making regarding investments in specific products
  • Built product recommendation system for investors leading to 10% increase in conversion rate, forecasted to bring in around 2,000,000 dollars in investment in 2024
  • Setup API services in AWS to run ML models in cloud and feed data back to salesforce for decision making
  • Automated the process of founders data collection from sources and creation of deals and EOI pages saving 80 hours of human effort every week
  • Constructed and implemented data pipelines on AWS to execute ETL processes, crucial for feeding data into machine learning models
  • Developed an API through Google Cloud Platform (GCP) to automate the updating of Google Sheets with new leads, thereby streamlining the process of sharing crucial information with founders
  • This initiative significantly contributed to increased conversions and revenue growth
  • Implement AWS Lambda and Fargate serverless architectures wherever possible for the efficient deployment and triggering of APIs, optimizing for reduced operational costs and improved scalability.

Data Engineer

ProUnlimited
01.2021 - 01.2023
  • Designed detailed SQL reports visualizations for fortune 500 clients Apple, , Siemens, Genentech
  • Achieved an accuracy of 92.3% Dense Neural Network model, 87.4% Random Forest Model with lower latency period while matching candidates to jobs vice versa in Python Linux
  • Programmed Matching services API by leveraging deep learning models Tensorflow, Keras, Sklearn to match 1000's of candidates to jobs
  • Implemented Natural Language Processing tools for extracting information from resumes, job descriptions with 95% veracity
  • Reduced companies reliance on third party tool and minimized cost for resume and job parsing by leveraging NLP tools Spacy, NLTK, Gensim to build in-house resume and job description parser
  • Delivered exploratory data analysis reports, helped find gaps in organisational processes and improve application rate by 15%
  • Generated performance graphs for websites, visitors, pages visited, actions performed, time spent by employing Web Analytics tools Matomo, Pendo improving stickiness metrics by 11%
  • Built a chatbot (integrated with database for storing data through web hook) to answer queries and engage 100's of people to apply for jobs
  • Deployed Matching services, Chatbot, Parsers, ML models by employing libraries such as Flask, Swagger, Docker
  • Created end to end data science products with containerised model deployment to AWS using Jenkins via Flask API, Classifying thousands of internal HR query data into similar categories by implementing ML algorithm K-Means, TF-IDF
  • Launched chatbot utilizing Dialogue Flow algorithm to train NLP models with classified data and answer internal HR queries.

AI/ML Engineer

Ford Motor Company
09.2020 - 01.2021
  • Classifying thousands of internal HR query data into similar categories by implementing ML algorithm KMeans, TF-IDF
  • Launched chatbot utilizing Dialogue Flow algorithm to train NLP models with classified data and answer internal HR queries.

Education

Master of Data Science -

Deakin University
07.2021

Bachelor of Mechanical Engineering -

Osmania University
06.2018

Skills

  • Python R
  • SQL PostgreSQL NoSQL
  • Machine Learning Deep Learning
  • Natural Language Processing Text Analytics
  • Tableau Power BI
  • Flask Django
  • Docker Kubernetes
  • AWS G-Cloud DataBricks

Timeline

Senior Data Engineer

VentureCrowd
01.2023 - Current

Data Engineer

ProUnlimited
01.2021 - 01.2023

AI/ML Engineer

Ford Motor Company
09.2020 - 01.2021

Master of Data Science -

Deakin University

Bachelor of Mechanical Engineering -

Osmania University

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Ausaf QS