Manas Joshi Portfolio

Intro

Hello! I'm Manas Joshi, a recent graduate majoring in Business Analytics and Project Management from the University of Connecticut. As a data science enthusiast, I bring a strong IT background and proficiency in Python, SQL, and data visualization tools. I'm actively seeking roles in Data Analytics, Pricing Analytics Data Science, and Business Intelligence, armed with expertise in statistical analysis, machine learning, and project management. My experience as a Pricing Analyst has honed my analytical skills and business acumen. Let's connect and explore how I can contribute to data-driven decision-making in your organization!

My passion for coding began at a young age and has only intensified over time, with a particular focus on Data Science and Analytics. My experience working in the technology divisions of multinational corporations such as Tata Consultancy Services and General Electric Appliances has provided me with invaluable industry insights. As we witness the ever-growing integration of businesses and information technology, I am committed to leveraging my expertise in order to bridge the gap between technology and business effectively.

Work

1. Pricing Analysis and Strategy Enhancement:

• Led collaborative efforts across diverse teams (Technology, Marketing, Sales, Finance, and Project Management) to conduct in-depth pricing trend analysis, driving a 20% increase in gross profit and optimizing product margins by an impressive 12%.

2. Data Integration and Process Optimization:

• Transformed data extraction and integration processes, migrating from MS Excel to Tableau and leveraging Vertica database. Achieved an 80% reduction in manual efforts, executed advanced SQL queries with multiple joins for SKU insights, resulting in an 18% boost in overall profitability.

3.Quantitative Analysis and Price Elasticity:

• Implemented a targeted Price Elasticity Model for SKU promotions, empowering stakeholders with quantitative insights. This initiative significantly elevated decision quality, leading to a 30% increase in profit-driven promotional choices and reinforcing a reputation for sharp pricing decisions and enhanced company profitability.

1. SQL Performance Optimization:

• Designed and implemented highly efficient SQL queries for complex data analysis, significantly improving data processing speed. This meticulous approach not only enhanced database performance but also facilitated more streamlined and insightful decision-making processes.

2. Advanced Analytics and Visualizations using Tableau:

• Developed and maintained Tableau reports and dashboards that played a pivotal role in business intelligence. Leveraged Tableau's capabilities to present key performance indicators (KPIs) such as Scalability, Speedup, and Memory-usage. This visual approach not only provided actionable insights but also contributed to a 20% improvement in overall business performance.

3. Efficient Process Improvement Analysis:

• Demonstrated excellence in project coordination and resource management as a lead in the design and implementation of GPU-based ML algorithms. Utilized agile project management methodologies to achieve a substantial 50% reduction in data processing time, thereby streamlining workflows, enhancing efficiency, and contributing significantly to improved data-driven decision-making

Education

• MS in Business Analytics and Project Management - May 2024,University of Connecticut

• Bachelor of Technology in Information Technology - July 2021, SGSITS

Skills

• Analytical Skills:

  Statistical Analysis, Data Integration, Cleaning and transformation, Data Modeling, Data Storytelling, Dashboard development, A/B testing, Data Analysis and Visualization, Causal Inferencing, Time Series Analysis & Forecasting, Text Analysis,NLP

• Tools & Frameworks:

  Python (NumPy, Pandas, Scikit-learn, Matplotlib, PySpark), R, SQL, MS Office Suit (Excel, PowerPoint, Word, Access, Teams), Git/GitHub, Google Colab, SAS, Google Analytics, Adobe Analytics, Linux, Alteryx, Informatica

• Databases:

  MYSQL, MongoDB, Google Big Query, Oracle, MariaDB, SSMS

• Project Planning and Management:

  RACI Matrix, Stakeholder and Client Management, MS Project, JIRA, Lucid Chart, Gantt Chart, Kanban, XP

Certifications

Advanced SQL Assessment

Issued - February 2023

Confirms proficiency in advanced-level SQL, a key asset for efficient data querying and analysis in a data analyst role.

Introduction to Tableau

Issued - April 2023

Builds foundational Tableau expertise, essential for creating impactful visualizations and enhancing data analysis effectiveness.

INTERMEDIATE PYTHON

Issued - January 2023

Showcases advanced Python skills vital for data analysis and manipulation

Alteryx Machine Learning Fundamentals

Issued - November 2023

Develops foundational proficiency in Alteryx Machine Learning, equipping with essential skills for effective model development and data analysis

1. 2023 Travelers Analytics Case Competition (InsNova Auto Insurance Company Modeling Problem)


• Overview - Participated in the 2023 Travelers Analytics Case Competition, focusing on enhancing the predictive modeling of auto insurance claim costs for InsNova Auto Insurance. The project aimed to improve pricing accuracy, risk segmentation, and competitive market positioning.
• Data Analysis - Handled a dataset with over 22,000 entries, performing preprocessing tasks like handling missing values and standardizing data.
• Feature Engineering -utlized algorithms such as SelectKBest for effective feature selection, identifying variables critical for predicting claim costs.
• Model Development - Explored multiple Regression models, including Linear Regression, Random Forest, Decision Tree, and Gradient Boosting achieving significant MSE and R2 improvements.
• Business Impact - Focused on a balance between model accuracy and interpretability to enhance understanding of variables affecting premiums.
• Result - The experience sharpened my analytical skills and provided valuable insights into challenges and techniques of predictive modeling in insurance.
2. Walmart Sales Forecast

• Overview - This project aimed to develop a model for predicting sales at Walmart stores, enabling proactive inventory management, accurate revenue forecasting, and strategic decision-making.
• Data Analysis -
  • Explored seasonal trends, identifying varying sales patterns across departments and store types.
  • Analyzed individual holiday impact, revealing key sales periods like Christmas, Thanksgiving, and Black Friday.
  • Assessed the influence of economic indicators (CPI, temperature, unemployment, fuel) with no significant observed impact on weekly sales.
• Feature Engineering - Encoded categorical features for improved model understanding and addressed data non-stationarity using difference, log, and shift techniques.
• Model Development -
  • Evaluated various models: Random Forest Regressor, ARIMA, Exponential Smoothing, and ARCH.
  • Achieved the lowest error (821 WMAE) with Exponential Smoothing.
  • Identified limitations of assigning Christmas sales to the last week of the year, advocating for the 51st week.
• Business Impact -
  • Enhanced inventory management by anticipating sales variations.
  • Improved revenue forecasting accuracy, driving informed business decisions.
  • Supported strategic planning by identifying key sales periods and department-specific trends.
• Results -
  • Developed a reliable sales forecasting model with actionable insights.
  • Gained valuable understanding of seasonal and store/department dynamics.
  • Demonstrated expertise in data analysis, feature engineering, and model selection.

Contact

Let's Connect

I'm always open to new opportunities and collaborations. Whether you're interested in discussing potential projects, job opportunities, or just want to connect and chat about data, feel free to reach out. I look forward to connecting with you!

• LinkedIn
• GitHub
• Kaggle
• HackerRank

Elements

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