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Rahul (RID : c94qleicwgld)

designation   Analytics Engineer

location   Location : Gurgaon, India

experience   Experience : 7 Year

rate   Rate: $18 / Hourly

Availability   Availability : Immediate

Work From   Work From : Offsite

designation   Category : Information Technology & Services

Shortlisted : 1
Total Views : 137
Key Skills
Tableau Python Data Pipelining

Rahul Sharma

Analytics Engineer


Analytical, accomplished professional with over 7 years of experience in multifaceted roles requiring project management, business development, and solutions. Skilled in the areas of Machine Learning, DeepLearning, Statistics, Python, data warehousing, and data analytics. Motivated and eager to advance my career with a growth-oriented, technically advanced organization.


Machine Learning (Linear and Logistic Regression, XGBoost, GBM, Decision Trees, Clustering.) Deep Learning (Tensor½ow 2.0, CNN, RNN, NLP Fundamentals, Computer Vision, OpenCV) Statistics (Hypothesis Testing, Descriptive statistics, Inferential Statistics, Sampling, t test, A/B testing) Python (sci-kit learn, pandas, data structures, numpy, matplotlib, seaborn)

SAS (PROC, Data wrangling, Data manipulation, Univariates)

Tableau (Variable creations, functions, data visualization, calculated kelds, Measures and Dimensions) Apache Spark (Pyspark, Elastic map Reduce, MLlib, Spark SQ, Big Data framing and analysis) DataBricks (MLFlow, AirFlow, AutoScaling) | AWS | Postman | GIT | Docker


Data Scientist

Webority Technologies

Working as a ML & DL expert(R&D) in the Product Development team(AIQ) to create a global product which can be marketed as a recommendation engine for multiple clients.

Mainly Worked on Offer Recommendation models by creating automated feature extraction python class and using LSTM and bidirectional GRU's for the training purpose.

Contributed meaningful enhancements to existing models through careful directed research.

Direct involvement with the client CTO to improve Customer engagement by providing insights and recommendations and creating models for predicting customers more likely to register and use Auto-Pay to pay their premium(Random Forest Classiker).

Increased customers in the Auto-pay bucket and hence reduced the customer executive calls to multiple customers for paying premium, resulting in 7% increase in on-time payment.

Developed Fraud and Risk Models, New business and Early Lapse Models for an Insurance clients using GBM and XGBoost. Decreased Frauds by 17% when compared to same time last year.

Developed and Productionized various ML models to optimize different verticals of the company.

2016 – present

Worked with multiple clients from different domains including Insurance, Logistics, Petroleum, FMCG and CPG and created ML models based on differenct algorithms like Cluster Analysis, Logistic Regression, XGBoost, Random Forest for predicting attrition and targeting audience. Worked on Campaign measurements, Segmentation and prokling. Dashboard reporting through Tableau.

Petroleum Client - A/B testing and hypothesis testing to evaluate the offers performance

Logistic Client – Responsible for Delivering reports, creating Offers for the Premium Segment customer using VAP Segmentation and using Logistic Regression and XGBoost Model for attrition.

American Insurance Client – Develop Tableau/Excel Dashboards for their Home insurance, Auto and Life insurance verticals, used SAS for data creation.

FMCG Client- Create MOA(Market Opportunity Analysis) based on KMeans cluster algorithm to segment into different groups and knd opportunities to target the Audience. Also provided strategy on customer engagement using Market Basket Analysis.

Developed and run Pipelines in GoCD using AWS and Apache Spark services for scalable Productionization of models.

Maintain the latest code in GIT.

Trained on Databricks to migrate the current models to Databricks.

Increased Line Of Business from 2 to 4 after the insightful dashboards provided to the client.

Automated Data analysis and visualization pipeline with Python.

Designing and constructing the prototypes for various experimental setups including the implementation of test and control.

Adhoc request from clients for small analysis. Programming languages used Python, SAS,R, PySpark.

Increased client engagement with the company, leading to more business from the clients.

Trained and managed 3 new graduates for 8 months. Won 2nd Price in 2021 Epsilon Data science Hackathon.

Technical Operations Analyst


Mostly worked on shell scripting and scheduling of various server activities so that there is no human error to be made.

Reduced manual work by 35% which led to other enhancements and opportunities for work with the company.

Worked with a telecom giant of Saudi Arabia – Mobily. Managed database with Postgres SQL.

Used python and Shell scripting to automate the tasks.

2015 – 2016


Bachelor of Technology in Computer Science Engineering

Galgoíias Universiíy

2011 – 2015

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