Jignesh Kirti Nagda

About

Experienced Data Scientist adept at leveraging advanced analytics and machine learning techniques to derive actionable insights from complex datasets. Skilled in Python and SQL, with a proven track record of driving business value through data-driven decision-making.

Experienced Data Analyst & Aspiring Data Scientist

Passionate about tackling challenging problems and driving innovation in data-driven environments.

Birthday: 13 September 1997
Website: https://radioactive17.github.io
Phone: +1 812-778-5895
Email: jigsshah.97@gmail.com

Age: 26
Highest Degree: Master of Science
Location: USA
Languages: English, Spanish, & Hindi

Resume

Sumary

Jignesh Kirti Nagda

Data-driven Data Scientist with 2 years of experience crafting and optimizing data models to extract meaningful insights and drive strategic decision-making. Proficient in developing advanced analytics solutions to solve complex business problems, with a focus on delivering actionable recommendations for informed decision-making.

(812) 778-5895
jigsshah.97@gmail.com

Education

Master of Science - Computer Science

2022 - 2024

Indiana University Bloomington, Bloomington, IN, USA

GPA: 3.8/4

Relevant Couresework: Elements of AI, Applied Machine Learning, Data Mining, Applied Database Technologies, Computer Vision, Data Visualization

Bachelor of Technology - Information Technology

2017 - 2021

University of Mumbai, Mumbai, MH, India

CGPA: 8.5/10.0

Relevant Couresework: Applied Mathematics, Data Structures & Algorithms, Object Oriented Software Engineering, Advanced Databases, E-Commerce & E-Business, Business Analytics, Big Data Analytics, Cloud Computing, Software Project Management, Software Testing & Quality Assurance

Professional Experience

Business Intelligence Developer

September 2024 - Present

TFI Family of Companies, Topeka, KS, USA

Led the transition of 9 legacy tabular reports to Power BI for a child welfare services non-profit, enabling real-time insights and eliminating additional analysis, while ensuring data health and scalability with Azure.
Performed in-depth analysis of organizational data using SQL Server, uncovering operational inefficiencies and opportunities for improvement, streamlining processes to boost efficiency, and driving a 23% increase in organizational performance.
Conducted special projects, including trend analysis and predictive modeling using Python, supporting strategic initiatives.
Collaborated with cross-departmental teams to identify data discrepancies and reduce data entry errors, partnering with developers to enhance organizational software modules, preventing future errors, and improving overall data quality by 15%.

Research Data Analyst

January 2024 - September 2024

Indiana University, Bloomington, IN, USA

Executed genome-wide association analysis using advanced statistical methods to identify genetic variants associated with Alzheimer’s risk, leveraging Python and R to analyze large datasets, contributing to advancements in neurodegenerative research.
Processed and cleaned over 100 GB of genomic data using Plink and Python, ensuring data integrity and HIPAA compliance, which improved analysis accuracy and supported critical research initiatives.
Engineered 5 ETL pipelines using Python (NumPy, Pandas, SQLAlchemy) to load 10 years of CDC’s NHANES data into PostgreSQL, automating with Airflow to reduce manual effort and enabling faster, more accurate analysis.

Managed and retrieved large datasets efficiently using SQL by creating indexes on frequently queried columns, optimizing queries, and writing parameterized stored procedures, resulting in a daily time saving of over 35 minutes.
Conducted regression analysis on iron biomarkers and health metrics using Scikit-learn and Statsmodels, identifying factors affecting COPD. Delivered insights with a 30% explanation of variance, supporting strategic decision-making.

Data Analyst

June 2021 - July 2022

Laundriz Development India Pvt Ltd, Mumbai, MH, India

Led a cloud migration project for a consumer services startup leveraging Azure Data Lake Storage and Azure Databricks achieving an 87% reduction in infrastructure costs, a 37% improvement in data access speed, and enhanced scalability for advanced analytics.
Developed custom Power BI dashboards to track key performance indicators (KPIs) in real-time, reducing service delivery times by 1.5 hours daily and enabling immediate corrective actions to improve operational efficiency.
Formulated SQL queries to support ad-hoc reporting needs, enabling quick and flexible data retrieval for various business requirements.
Analyzed customer churn data with EDA & predictive modeling to identify key churn patterns, increasing retention rate by 12%.
Analyzed historical data using SQL and visualization tools to identify customer trends and opportunities, partnering with marketing and product teams to develop data-driven strategies that acquired 3,500 new customers in a single quarter.

Data Analyst Intern

August 2020 - January 2021

Ticekt On Go, Mumbai, MH, India

Developed interactive Tableau dashboards and SQL-based reports for a SaaS company to monitor app performance and customer satisfaction metrics, enabling the product team to identify trends and increase user engagement by 6%.
Optimized data pipelines by integrating app usage data from AWS into MS SQL Server, reducing query processing time by 35% and enabling real-time analytics to support business decisions.
Developed time series forecasting model in Python to analyze ticket sales trends, delivering insights that optimized marketing strategies and increased ticket purchases by 11%.
Analyzed user behavior data using Python to identify checkout bottlenecks, collaborating with the development team to optimize the app’s interface, reducing checkout time by 1.5 minutes, boosting user satisfaction.

Software Engineer Intern

January 2020 - July 2020

KJ Somaiya College of Engineering, Mumbai, MH, India

Engineered and implemented a database schema in PostgreSQL for an EdTech project, optimizing data handling for 1M+ records.
Crafted backend in Django, processing 2000+ grade submissions per hour and enhancing overall system responsiveness.
Reinforced data security measures by implementing 2FA and secure access protocol, safeguarding sensitive data for over 1,000+ faculty members with zero security breaches during the internship.
Led testing for software modules, identifying and fixing 20+ vulnerabilities, ensuring a reliable and secure grading process.