Data Analyst Machine Learning

Prachetan Reddy Soddum

************@*****.*** 205-***-****

https://www.linkedin.com/in/prachetan-reddy-soddum-b7b572287/

A Data Analyst with 4 years experience in Data Analytics and Data Engineering, expertise in using machine learning algorithm (supervised and Unsupervised learning) for Data Analysis tasks. Skilled in Maintaining databases and handling data migration tasks. Experience in Building Dashboards and reporting using BI tools.

RELEVANT EXPERIENCE

LTI

Data Analyst - Fraud Analyst June 2020 – Aug 2023

•Reviews, verifies, and/or identifies identity theft to detect/ prevent financial crimes activities, policy violations, and suspicious situations in order to mitigate and/or recover losses.

•Create rules to stop the fraud account opening by identifying the patterns thru Data analysis and Data Science techniques.

•Monitoring the trends and suspicious accounts and taking necessary action in case of a sudden spike

•create alerts based on the data available for the accounts and request additional necessary documents to validate the account.

•Creating ETL jobs for the accounts and applications monitoring in Cloudera workbench and using power bi to see the visual trends.

•Extensive Focus on Small Business space, monitoring check deposits, alerting suspicious deposits and creating rules to capture fraud by maintaining low false positive rate.

•Migrated data from Cloudera to AWS into Snowflake using Snow pipe, Stream and Task together.

•Created daily job stream to load the data from S3 external bucket to snowflake datalake using Snow Streams and Tasks.

•Work closely with legal groups and help them provide the data involving decision making process.

•Built Small Business Origination Model using Decision Tree algorithm to screen the new accounts

•Monitoring the trends using BI reporting and identified areas for the process improvement.

•Creating ETL jobs for the accounts and applications monitoring in Cloudera workbench and using power bi to see the visual trends.

•Build CI/CD pipelines to extract the payload data and perform dynamic JSON parsing to bring the structural format to the data.

•Maintain the SQL server Database and ensure the data consistency and profiling is maintained.

•Designed and Developed dynamic stored procedures and Triggers to automate the reporting process.

•Conducted User Acceptance Testing (UAT) for releases and patches, ensuring thorough review of functionality.

•Implement DAX commands and performed several actions using Power Query Editor to achieve the visual functionality.

•Integrated the dashboards into Microsoft Dynamics and shared the reporting to the FCU leadership team

•Write Pyspark and Python scripts and setup a daily CRON job to process the previous day data after the Batch processing.

LTI

Data Analyst Intern Jan 2020 – June 2020

•Report actionable, statistical and analytical insights to executives for effective decision making.

•Maintained large database and used professional statistical methods to collect, analyze and interpret results by visualization tools.

•Write python scripts to automate the daily tasks, data extraction and data cleaning by executing the CRON jobs

EDUCATION Master of Science in Computer Science Aug 2023- Dec 2024

Concordia University St Paul

TECHNICAL SKILLS

Programming Languages/ Frameworks: Python, SAS, PYSPARK, AWS, HTML, XML, CSS, Node.JS,D3.JS,COBOL,FLASK,Django

Database: SQL:DB2, PostgreSQL, MYSQL, NOSQL: MongoDB, Apache Cassandra

Tools: Anaconda, Tableau, GitHub, Visual Studio, Power BI, MICROSOFT DYNAMICS, SAS, Excel, ETL(Informatica), SPLUNK, HUE, IMPALA,HIVE,SNOW FLAKE

Methodology : Agile, waterfall

CERTIFICATIONS

AWS Solutions Architect Certification July 2021 – July 2024

Skills: EC2, VPC, RDS, S3, Lambda, ECS, IAM, Cloud Front, Snow Flake, DynamoDB, Route53, Redshift, Sage maker

Data Analysis and Machine Learning with Python May 2020 – till date

Skills: Regression, Bagging (Random Forest, Decision Tree), Boosting (XG Boost, Cat Boost), Clustering, Neural Networks (ANN,CNN,RNN)

RELEVANT PROJECTS

Customer Segmentation and Market Basket Analysis

•Implementation customer segmentation using Clustering based on RFM metric. Used Association rule mining algorithms like FP-growth, ECLAT and Apriori for frequent item set mining.

Machine Translator using GRU, RNN using Embedding, Bidirectional RNN and Deep RNN

• Implemented simple RNN using GRU,RNN using Embedding, Bidirectional RNN to convert text from English to French, Finally stacked all these algorithms and constructed Deep RNN which has achieved highest accuracy.

Product review Sentiment Analysis using MNB, Logistic Regression, LSTM and deployed best models using Flask

•Implemented Multinomial Naïve Bayes Model using Count vectorizer and TF-IDF vectorizer as feature extraction technique.

•Implemented a pipeline model which has TF-IDF and logistic regression using Grid search to get best parameters.

•Implemented LSTM model using tokenizer and word2Vec embedding with hyperparameter tuning.

Interactive COVID 19 Tree Map and US map visualization

•Developed an Interactive week wise Covid-19 Tree Map Visualization. A lollypop chart will be displayed to see continent wise covid cases.

•Click on to see the visualization - https://pr365.github.io/covid-treemap-/

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