Dec 2020 – Jul 2021 · 7 mos

• Key Projects:
• ☑ DSMONITOR | CPG Domain | Lead Data Scientist | Mentored Data Engineers and Data Scientists
• The high voltage project proved the DS Expertise for Fractal.
• The DSMONITOR project intends to bridge the gap between the Data Scientists and the MRO so that the models can be deployed in Production rather than getting failed in the POC stages.
• Feature Quality checks: This checklist shall ensure a good understanding of the data and possible use cases – and shall be stored within every Data Science project repository.
• Model Quality checks: This checklist shall ensure quality models are used that are fit for the business case and they follow the best practices.

Jan 2018 – Dec 2020 · 2 yrs 11 mos

• Working on deploying scalable AI solutions in GCP.
• ☑ Upsell and CLTV | Played an active role in building upsell models in serverless, parallel and distributed processing in GCP using logistic regression and RF models and also built the whole pipeline using Airflow and it is in live for 20 products, 10 million customers, across 3000 retail and call agents.
• ☑ Customer retention and Churn | Developed a highly scalable churn model that harmonized terabytes of data from various raw data sources and built a holistic view of customers and hence predicting the chances of churn and their net revenue in the near future.
• ☑ Data warehousing | Developed data marts and customer 360 information for Campaigns team using complex joins and optimal subqueries
• Technical Skills: GCP Data Engineering, Machine Learning [A-Z], Deep Learning hands-on, ML using Tensorflow, SCRUM master certification.

Jun 2016 – Dec 2017 · 1 yr 6 mos

• ☑ For a German conglomerate company using sensor data, Tasked with finding the gear break down point and detect anomalies using PySpark.
• ☑ Piracy Analytics project to Identify the license is Pirate or Legitimate. It is basically a Code Migration project, Migrating the existing codes from SQL to Spark SQL. Built Machine Learning models in Spark.
• ☑ I also worked on crawling data for sites like Reddit and Twitter and did topic modeling in NLP.
• Technical Skills: Scala (Advanced), Python(Advanced), R(Advanced), Linux, Apache Spark, Probability and Statistics, SPSS and Excel for Beginners
• Spark- ML, RDD, DataFrames and SQL.

Apr 2016 – May 2021 · 5 yrs 1 mo · Hyderabad, Telangana, India

• 1. I have given freelance data science and spark training across geographies like India (Bengaluru ) and UK (London).
• 2. I have conducted meetups and long talk day sessions in Machine Learning.

Dec 2015 – May 2016 · 5 mos · Bengaluru, Karnataka, India

• Worked in a performance comparison of handheld devices across hybrid platforms like Cordova, ioS applications and Android applications

May 2015 – Jun 2015 · 1 mo · Greater Chennai Area

• A semi-supervised learning-based approach to Sentiment analysis. The task is to classify the sentiment score’s whether positive or negative. A semi supervised based approach to sentiment analysis was proposed. Co training and Co testing experiments were carried in Python.

May 2014 – Nov 2014 · 6 mos · Delhi Ave

• Learning Representations using Deep Learning:
• 1) Developed a Deep Independent Component Analysis model
• 2) Got two views for a given dataset, so that we can try semi-supervised approaches on it.

May 2013 – Jul 2013 · 2 mos · Coimbatore

• Recommender Systems - Collaborative filtering:
• Developed a Recommender system based on collaborative filtering for the GroupLens dataset. The goal is to predict the values of the users who have not rated it. Techniques like Matrix Factorization were used.