JUNAID ZULFIQAR
MACHINE LEARNING ENGINEER
PROFILE
As a Machine Learning Engineer, Proficient in creating data regression models, utilizing predictive modeling, and
analyzing data mining algorithms to deliver actionable insights for complex business problems. Involved in python open
source community and passionate about deep reinforcement learning.
SKILLS
Machine Learning, Deep Learning, Reinforcement Learning, Data Analysis, ETL-Pipelines, PowerBi, Web
Development, Computer vision, Natural Language Preprocessing, Data Mining, Web Scraping, Web Automation,
Data Visualization, RestAPI, DataBricks, HDFS, Data Streaming
Databases (SnowFlake, SQL Server, MySQL, Mongo DB, PostgreSQL)
Azure (Synapse, Storage Account, data factory, virtual Machine, ML Studio, delta lake, etc) AWS (S3, Kinesis,
EMR, SageMaker, Lambda, Glue, Athena, EC2, VPC , Redshift, delta lake, etc). Programming Languages ( Python,
SQL, Pyspark, C++, Javascript, HTML, CSS)
WORK EXPERIENCE
Brickclay | July 2022- Current
Machine Learning Engineer
Developed and implemented a customer retention forecast model using machine learning algorithms, to find out
the reason behind the lost customers' interest.
Designed and deployed a recommendation system that personalized product offerings for individual customers,
leading to increase in cross-selling and upselling opportunities.
Built a customer segmentation algorithm by utilizing ML techniques to identify high-value customer segments,
enabling targeted marketing campaigns and improving customer retention.
Developed a forecasting tool to analyze revenue and accretion variance, bussiness pipelines, market and industry
trends.
Worked with clients to understand bussiness needs and convert those needs into actionable reports in powerbi.
Used AWS EMR and Glue to transform and move large amounts of data into and out of other AWS data stores
and databases, such as Amazon Simple Storage Service (Amazon 53), Data Catalog, Relational Database Services
(RDS), Redshift and Snowflake.
Brickclay | July 2022 - Current
Machine Learning Engineer
Implemented AWS Step Functions to automate and orchestrate the Amazon SageMaker related tasks such as
publishing data to S3, training ML model and deploying it for prediction.
Worked on Azure Data Factory to integrate data of both on-prem (Mongo DB, SQLServer) and cloud (Blob
storage, Azure SQL DB) and applied transformations to load back to Azure Synapse and makes pipelines for data
engineering and machine learning task.
Good Understand of Spark Architecture including Spark Context, Spark-SQL , Dataframe API , Spark Streaming,
MLlib , and Pair RDD.
Created and configured Snowflake warehouse strategy to move a terabyte of data from S3 into Snowflake via PUT
scripts. Loaded data from AWS S3 bucket to Snowflake database using Snowpipe.
Work with Data Engineers to determine how to best source data, including identification of potential proxy data
sources, and design business analytics solutions, considering current and future needs, infrastructure and
security requirements, load frequencies, etc.
Hands on experience on Unified Data Analytics with Databricks, Databricks Workspace User Interface, Managing
Databricks Notebooks, Delta Lake with Python, Delta Lake with Spark SQL.
Synergic Professionals | July 2021 - July 2022
AI Developer
Automate and OCR their incoming invoices and CNIC cards through an intelligent solution that extracts the fields from
the documents and creates the corresponding transactions in the ERP system accordingly.
Develop API services in an Agile environment to automate the 2-way PO matching and 3-way PO matching
process.
Creating Chatbot's for their residential, and commercial customers to provide various types of general and
enterprise business information. These bots have features like voice - to - text and vice versa.
Review customer's debit and credit card transactions, specifically focusing on invoices, to evaluate potential fraud.
Analyze commercial accounts for fraudulent activity related to invoices through multiple card processors to
mitigate fraud loss
Maintain accurate records containing known data triggers to support identification of fraudulent activity in invoices.
Developed and implemented NLP models for sentiment analysis, entity recognition, relation extraction, etc.
Developed Machine learning based services like background remover, social media
(youtube, instagram, facebook) Video downloader, Text summarizer, Paraphrazer, Article generator and Grammer
checker by collaborating with other developers.
Good Understanding of scraping and automating dynamic or forbidden websites.
