Sagar Paresh Vora
Data whisperer: I make sense of the chaos
I am an aspiring Data Professional with expertise in Data Analysis and Science, translating insights into impactful solutions through hands-on projects. Demonstrating a commitment to practical applications and real-world problem-solving, I am poised to contribute dynamic skills and innovation to the ever-evolving data landscape.
In my professional journey, I harness the power of data, unveiling patterns, shaping decisions, and illuminating the path to informed innovation.
About Me
Insightful Data Guy
As a recent graduate with a Master’s degree in Statistics from California State University – East Bay, I am deeply passionate about data science. My fascination lies in uncovering patterns and insights from complex datasets. I am eager to transition theoretical knowledge into practical applications and contribute to real-world projects. The dynamic and ever-evolving nature of data science captivates me, and I am excited to embark on a journey where I can apply my skills and continuously learn from impactful experiences.
I firmly believe that, “Data is not just numbers; it’s the silent storyteller waiting to unfold its narrative, and in the hands of a skilled data scientist, it becomes the compass guiding us through the uncharted territories of knowledge.”
- Sagar Paresh Vora
- +1(510)786-7216
- sagarvora671@gmail.com
Education
Master of Science in Statistics - Data Science
California State University - East Bay (2022 - 2023) (GPA: 3.92/4.00)
Relevant coursework: Linear and Logistic Regression, Probability and Statistical Theory, Statistical Methods, Data Visualization, Advanced R for Data Science, Analysis of Variance Models, Time-Series, Intro to Applied Deep Learning
Electronics & Telecommunication Engineering
SFIT, Mumbai University (2017 - 2021)
Relevant coursework: Data Analytics, Project Management, Machine Learning, Data Warehousing, Data Modeling, Data Cleaning.
Experience
Data Analyst
LifeSpheres (May 2024 - Present)
- Spearheaded a transformative overhaul of health data processing, optimizing ETL operations with MySQL, PostgreSQL, and Oracle databases.
- Orchestrated the integration of disparate healthcare data sources to streamline data collection and preparation processes, resulting in a remarkable 60% surge in predictive accuracy through the implementation of advanced Data Analysis and machine learning techniques in Python.
- Innovated data visualization strategies to provide stakeholders with intuitive access to critical healthcare metrics.
- Achieved a 79% increase in stakeholder engagement by creating interactive Tableau dashboards and reports, concurrently driving efficiency gains through adherence to health code standards in dashboard design.
- Collaborated closely with internal teams and clients to gather healthcare data, prioritizing data integrity and alignment with organizational objectives, while applying rigorous statistical methodologies to uncover actionable insights from complex healthcare datasets.
- Positioned the healthcare organization for future success by leveraging cutting-edge data analytics technologies and methodologies.
Teaching Assistant
California State University - East Bay (Jan 2022 - Dec 2023)
- Successfully leading and managing statistics tutorials for over 600 students, I showcased strong organizational and communication skills, creating an engaging and inclusive learning environment, while also demonstrating proficiency in Excel, Sheets, R-Studio, and Python to enhance the statistical learning experience and facilitate practical applications in coursework.
- Fostering a positive and collaborative learning community, I actively participated in departmental workshops, study groups, and tutoring initiatives. This dedicated involvement contributed to a noteworthy 20% improvement in student academic performance, demonstrating the impact of collaborative learning initiatives.
- Utilizing a data-driven approach, I assessed student progress, and identified trends, and areas for improvement, enabling the implementation of targeted strategies for enhanced understanding of complex statistical concepts. This resulted in a remarkable 25% increase in student success rates in examinations and coursework through the effective application of data-driven strategies and personalized support.
- Leveraged technology and multimedia resources to create engaging presentations, thereby enhancing the overall learning experience and promoting a deeper understanding of complex statistical concepts.
- Established a comprehensive support framework by providing personalized assistance during regular office hours, addressing specific challenges and inquiries related to statistical coursework, and executed a proactive outreach strategy resulting in a 15% reduction in students at risk of falling behind, fostering a more supportive and successful academic environment.
Business Analyst
Trimurti IML Solutions Private Limited (Mar 2019 - Dec 2021)
- Boosted supply chain processes, reducing operational inefficiencies by 15% and cutting manufacturing costs by 10%.
- Led data mining efforts to identify critical KPIs, enabling the board to focus on profitability and performance.
- Developed interactive Power BI dashboards that delivered actionable insights aligned with stakeholder requirements.
- Utilized Python libraries such as Matplotlib and Seaborn for advanced data visualization to support decision-making.
- Analyzed sales and production data to forecast demand, improving inventory management and reducing excess stock by 25%.
- Helped the company achieve significant cost reductions through data-driven insights and strategic recommendations.
Projects
Data Analyst (Freelancer)
R, Power BI (Mar 2024 - Sep 2024)
- Description:
- Conducted a comprehensive analysis of guest data, identifying distinct customer segments with specific preferences, and formulated targeted marketing campaigns tailored to each segment, resulting in increased bookings and revenue.
- Examined guest feedback and reviews to pinpoint areas for improvement, subsequently implementing strategic changes to enhance the overall guest experience, leading to positive online reviews and heightened booking rates.
- Analyzed historical data on events and seasonal trends to strategically plan targeted promotions, successfully executing these promotions during peak times, contributing to a significant boost in revenue.
- Developed and delivered regular, comprehensive reports to hotel management, highlighting key performance metrics and revenue growth, while fostering collaboration with the hotel team to ensure efficient communication and implementation of data-driven strategies.
- Analyzed historical data on events and seasonal trends to strategically plan targeted promotions, successfully executing these promotions during peak times, contributing to a significant boost in revenue.
- Through the strategic implementation of data-driven initiatives, the comprehensive efforts detailed above collectively propelled Sure-Stay Hotel in Vallejo to achieve an impressive 80% increase in overall profit, marking a transformative impact on the hotel's financial success.
Credit Card Fraud Detection
Python
- Description:
- Delving into the realm of cybersecurity, the Credit Card Fraud Detection Problem entails the modeling of historical credit card transactions, leveraging insights from known fraudulent instances. Employing Python, this project focuses on developing a robust model capable of discerning whether a new transaction is fraudulent. The overarching objective is to achieve an impeccable 100% detection rate for fraudulent transactions while meticulously minimizing the occurrence of incorrect fraud classifications. This pursuit of precision aligns with the imperative to fortify financial systems against potential threats, highlighting the integration of advanced analytics for enhanced security in the realm of credit card transactions.
- Outcome:
- Concluding the Credit Card Fraud Detection project, our methodical approach encompassed rigorous Exploratory Data Analysis and precise Data Preprocessing. Employing advanced modeling techniques, including Artificial Neural Networks, Random Forest, CatBoost, and XGBoost on meticulously curated training and testing datasets, we scrutinized the nuanced patterns between non-fraudulent (0) and fraudulent (1) transactions. The outcome of this exhaustive analysis unequivocally designates XGBoost as the optimal model, emphasizing its efficacy in discerning fraudulent transactions with unparalleled accuracy. This accomplishment underscores the strategic application of advanced analytics in fortifying financial systems, providing a resilient defense mechanism against credit card fraud.
London Bus Safety Analysis & Visualization
Tableau
- Description :
- Embark on a data-driven journey through London's bustling transportation network as I delve into the intricacies of bus safety. From in-depth analysis, I've identified key areas and insights, crafting an immersive experience through a live, interactive Tableau dashboard. This dynamic tool presents a comprehensive overview of bus accidents, empowering users to explore patterns, contributing factors, and high-risk zones. This visual narrative not only enhances comprehension but also fuels data-driven decisions, aiming to elevate safety measures and mitigate accidents in London's vibrant bus transportation system.
- "Uncover the pulse of safety in every click – explore London's bus accidents by borough for a data-driven revelation!"
- Outcome :
- In conclusion, my project culminates in a transformative live interactive dashboard, meticulously crafted in Tableau using London bus accidents data. This dynamic tool not only offers a comprehensive visualization of accident frequency but also empowers users to delve into specific boroughs, unraveling valuable insights. By navigating the interactive features, stakeholders can pinpoint patterns, contributing factors, and potential risk zones, laying the foundation for targeted safety strategies. With a mission to enhance awareness and facilitate data-driven decision-making, this project strives to make significant strides in mitigating accidents, ensuring the well-being of both passengers and pedestrians in London's intricate bus transportation system.
Football Matches Prediction
Python
- Description:
- Embark on a comprehensive journey through my portfolio as we delve into the intricate realm of predicting football match outcomes in the English Premier League (EPL). The project unfolds methodically, commencing with the scrupulous scraping of match data using requests, BeautifulSoup, and pandas. Following this, a meticulous data cleaning process ensues, preparing the dataset for machine learning applications with the adept use of pandas. Leveraging scikit-learn, we unlock the potential to predict match winners, navigating through historical data to unveil underlying patterns.
- Outcome:
- Rigorous error measurement becomes our compass for improvement, guiding us to refine our models continually and enhance predictive precision. This project stands as a testament to the seamless integration of data scraping, cleaning, machine learning, and continual refinement, offering a captivating exploration into the convergence of sports and data science within the esteemed English Premier League. Witness the evolution from raw data to insightful predictions, demonstrating not only technical proficiency but also a strategic approach to unraveling the complexities of football match forecasting.
Multiple Linear Regression for Car Price Analysis
R-studio
- Description:
- In the realm of car price analysis, Multiple Linear Regression emerges as a strategic ally, unraveling intricate relationships between various factors and the ultimate determinant—car prices. A meticulous curation process, eliminating variables with p-values exceeding 0.05, refines the model to include only the most impactful predictors. The ensuing refitting process optimizes model parameters, while a detailed examination of the scatterplot and validation against regression assumptions ensures reliability
- Outcome:
- This methodical approach yields a streamlined Multiple Linear Regression model, finely tuned for precise car price prediction. Strategic variable pruning enhances predictive accuracy, and visual scrutiny of the scatterplot enriches insights into data distribution. Rigorous adherence to regression assumptions underlines the model's reliability, affirming its efficacy in decoding the complex dynamics influencing car prices with confidence.
Sales Superstore Statewise Analysis and Visualization
Tableau
- Description:
- Navigating the dynamic retail landscape, I've harnessed the power of Tableau to meticulously craft a visually compelling sales strategy from intricate data. This project empowers executives at a major superstore chain, providing them with the agility to make nimble decisions. Tailored to identify and contextualize the worst-performing sub-categories in each region, my Tableau visualization seamlessly blends "pop-out" design principles, Gestalt Principles, and streamlined cognitive load. This ensures that meaningful insights not only come to life on the screen but also equip decision-makers to make a persuasive case for strategic moves. Welcome to a world where Tableau transforms data into a powerful ally, offering actionable insights for impactful decisions in the realm of retail.
- Outcome:
- In the journey through "Average Profits to Determine Sales Based on States," the exploration goes beyond static insights. By seamlessly integrating the ability to click and delve into different regions, this Tableau-driven odyssey becomes an interactive roadmap to understanding the dynamic trends in states. Unveiling the intricate dance between sales, profits, and average profit ratios, each click opens a gateway to regional nuances, empowering decision-makers to decipher the subtle shifts in the retail landscape. Welcome to a data-driven experience where every click is a step towards unraveling the ever-evolving story of success in the diverse realms of statewise sales analytics.
Get in Touch
I am available for communication between 8 am and 6 pm PST on weekdays and 10 am to 3 pm PST on weekends.
You can reach out to me via email, LinkedIn, or via phone during these hours.
I am prompt in responding and look forward to connecting with you during these designated time frames.
- sagarvora671@gmail.com
- +1 (510) 786-7216
- Linkedln | Sagar Vora
- Github | Sagar Vora
- Tableau | Sagar Vora