Machine Learning Engineer
Location : Delhi
Experience : 8 Year
Rate: $10 / Hourly
Availability : Immediate
Work From : Any
Category : Information Technology & Services
Rochit Ranjan
: +91-8825749283 : rochitranjan@gmail.com : github.com/rochitranjan
WORK EXPERIENCE
o Highly focused Data Scientist with 6 years of experience inclusive of 2.5 years of hands on
experience in Machine Learning, Data Science and Data Analysis.
o Have hands on experience of working on Packages like Scikit-learn, Statsmodels, Tensorflow, Keras.
o Have hands on experience in building standalone BOTS for text analytics using Python, pandas,
numpy, SQL, Core Java, NLTK, Scikit-learn, Spring Frameworks and Rabbit-mq.
o Good knowledge and hands on experience in handling large DataSets and Model building from
scratch to implementation.
o Data Science practioner and have completed a PG Diploma In Data Science from IIIT
Bangalore(June – 2019 to May-2020).
EDUCATION
2023-2025 : M.Tech (Aritifcial Intelligence and Data Science)
IIT – Patna
2019-2020 : PG Diploma In Data Science
International Institute of Information Technology, Bangalore
2010-2014 : B.Tech, ECE
The LNM Institute of Information Technology, Jaipur
Tools & Technologies
PROGRAMMING LANGUAGES : Core Java (Professional Efficiency), Python (Professional Efficiency)
DATABASES : MongoDB, MySQL, DB2
LIBRARIES, TOOLS & UTILITIES : Pandas, Numpy, NLTK, Scikit-learn, Statsmodel, beautifulSoup, Seaborn, Matplot,
Excel
PROJECT WORKS
Fitelo – (Machine Learning Engineer, June – 2023 to July – 2023)
o Completed building(from scratch) a User-user similarity system on the basis of their diseases and
diet consumption pattern.
o Completed building(from scratch) a diet recommendation system to find similar diets on the basis of
their nutrients and ingredients.
Tools and Libraries Used : Scikit-Learn, Pandas, Numpy, Scikit-Learn, Python, MongoDB
Cars24 Financial Services Pvt Ltd – (Data Scientist, May – 2021 to July - 2021)
o Collected and imported data from various data sources.
o Coducted exploratory data analysis on credit scoring data(CIBIL).
o Developed a weighted similarity based approach to do EMI estimation(libability) of customers
Tools and Libraries Used : Scikit-Learn, Pandas, Numpy, Scikit-Learn, Python, SQL
Landmark Group – (Associate Data Scientist, December – 2020 to Feb - 2021)
o Developed an ARIMA based model for forecasting weekly sales based on Color and shade
o Solved a business case to find out analogous product and predict weekly sales based on similar
product using KPrototype, Ordinary least squares and Bass Diffusion Model.
o Used WMAPE and rolling WMAPE as Evaluation metric.
o Used beautifulSoup to gather products competitors are selling.
Tools and Libraries Used : Statsmodels, Pandas, Numpy, Scikit-Learn, Python, SQL
Cognizant - QI BOTS (Machine Learning Engineer, January, 2015 to August, 2020)
o Built a ML model which finds the most similar historical ticket for a newly opened ticket using
Vectorisers(word2vec and Doc2Vec), Cosine and Jaccard's Similarity.
o Built a Topic Modelling model using Latent Dirichlet Allocation.
o Built a ML model for creating clusters of historical ticket using K-means.
o Worked on end to end migration of one entire BOT(Incident Ticket analyser) using python, Core java, Spring Boot,
pandas, NLTK, Sci-kit learn.
o Built a Trainer for Incident ticket analyser BOT which takes tickets within a stipulated time(given by user from UI)
and finds out tickets which are similar to each other.
o Built a scheduler for the BOT which takes newly opened tickets and finds out most similar previous incident using
text similarity techniques.
o Built two separate modules finding similarity of new tickets along with the existing open tickets and closed
tickets.
o Built ETL pipeline using Pandas, numpy and Python to fetch data from Database and bring them into Dataframe
format.
o Utilised flask to deploy models in the form of Rest end points.
o Added a Licensing module in application for computing the number of newly opened tickets processed.
Rochit Ranjan
: +91-8825749283 : rochitranjan@gmail.com : github.com/rochitranjan
o Familiar with message-broker system like rabbit-mq used for cross-platform interaction.
Tools and Libraries Used : Gensim, NLTK, Scikit-Learn, Pandas, Numpy, Python, SQL, Flask, Java, Spring-Boot
DATA SCIENCE CASE STUDIES
Domain : Acquisition Risk Analytics for Loans
o Objective: To predict whether loan should be granted to customer basis the customer detail provided
while filling the online form.
o Solution: Trained a Random Forest Classifier to predict whether loan should be approved or not.
o Key Achieveme
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