Consultant at Tiger Analytic. Data Engineer, Pharma, US HealthCare, Python, SQL
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Results-driven Data Engineer with 3 years of experience building scalable data pipelines and analytics frameworks using AWS, SQL, Python, and PySpark. Strong background in data modeling, ETL automation, performance optimization, and delivering high-quality datasets for reporting and business insights.
Bundelkhand University
Bachelor of science, Computer science and statistics
July 1, 2019 – August 1, 2022
B.B. Saraswati Vidya Mandir Inter College
Intermediate, PCM
April 1, 2018 – May 1, 2019
GDNDSN Inter College Karwi (Ashok Siksha Samiti)
High school
April 1, 2016 – May 1, 2017
Tiger Analytics
Analytics Consultant
April 1, 2026 – Present
Remote
Data Unveil
Data Engineer
May 1, 2025 – April 1, 2026
Data Unveil
Database Developer
June 1, 2024 – May 1, 2025
Jarvis Technology and Strategy Consulting
Data Analyst
November 1, 2023 – June 1, 2024
Delhi, India · On-site
Innomatics Research Labs
Data Analyst
December 1, 2022 – February 1, 2023
Remote
Movie Recommendation System
February 1, 2022 – May 1, 2022
📌Problem Statement & Business Objectives:- Using different techniques of Machine Learning, we need to build a Recommender System that recommends movies based on "Cast, Genre, Reviews, TMDB/IMDB ratings" • Data Collection: Gathered a diverse dataset of movies, including details such as genre, ratings, actors, directors, and user reviews, from various reliable sources. ⚫ Data Preprocessing: Conducted thorough data cleaning and preprocessing tasks, including handling missing values, removing duplicates, and standardizing the data to ensure its quality and consistency. • Exploratory Data Analysis: Performed exploratory analysis to gain insights into the dataset, such as distribution of movie ratings, popular genres which helped in understanding the underlying patterns. • Feature Engineering: Extracted relevant features from the dataset, including movie attributes, user preferences, and historical ratings, to create a comprehensive feature set for the recommendation system. • Collaborative Filtering: Implemented collaborative filtering techniques, including user-based and item-based approaches, to generate recommendations based on similarities between users or items. • Model Training and Evaluation: Utilized machine learning algorithms, such as matrix factorization and content-based filtering, to train the recommendation model. Evaluated the performance of the model using precision, recall, and accuracy. • Model Deployment: Deployed the recommendation system using Streamlit web framework, to create an interactive web application where users can input their preferences and receive personalized movie suggestions. • Documentation and Presentation: Documented the entire process, including data preprocessing steps, algorithm implementations, model evaluation, and deployment details. Presented the project outcomes, methodologies, and findings to the team and stakeholders, showcasing the value and potential impact of the Movie Recommendation System.
Applied data analytics
National Institute of Technology Raipur
June 25, 2026 – Present
HackerRank GOLD Badges (5⭐) in SQL & Python
HackerRank
June 25, 2026 – Present
data analytics
w3schools.com
June 25, 2026 – Present
SQL (Basic)
HackerRank
June 25, 2026 – Present
data analytics workshop
Jobaaj.com
June 25, 2026 – Present
Internship appreciation certificate
Innomatics Research Labs
June 25, 2026 – Present
Python for Data Science
Infosys Springboard
June 25, 2026 – Present
Machine learning using python
National Institute of Technology Warangal
June 25, 2026 – Present
Kaggle Bronze medal
Kaggle
June 25, 2026 – Present
Python programming
FutureSkills Prime
June 25, 2026 – Present
Probability and Statistics using Python
Infosys Springboard
June 25, 2026 – Present
Cultural Fit Analysis
The candidate has a diverse background spanning Data Analyst, Database Developer, and Data Engineer roles, indicating adaptability. The project on a Movie Recommendation System shows initiative and a passion for applying machine learning. The experience across different companies and roles, including an internship, suggests a willingness to learn and grow. However, the target role of 'Big Data Engineer' requires a deeper focus on distributed systems, advanced data warehousing, and real-time processing, which are not extensively detailed in the current experience. The 'Analytics Consultant' role starting in 2026 is in the future and cannot be evaluated for current fit.
Soft Skills & Operational Fit
The candidate's project descriptions indicate an ability to work on end-to-end solutions, from data collection and preprocessing to model deployment and documentation. The experience in automating report generation and building data quality platforms suggests a focus on efficiency and problem-solving. The role as a core team member in data analytics initiatives during elections implies an ability to work under pressure and deliver actionable insights.