Trishul Gowda Ashok (Trishul)
An introduction to Me!
I am a graduate student at the University of Cincinnati with a major in Business Analytics. I have around 4 years’ experience as a data analyst with a good amount of Analytics experience as well. I have thorough knowledge of the SAP ERP system and relational databases. I have experience working in R, SQL and visualization tools like Tableau. I have spent the last 4 years developing my data analysis skills.
I started off my career as a Data Analyst for a Real estate firm by name Properties in Mysore.
Here the analysis was done using previous sales, Expense and customer demographics data.
The analysis helped in answering questions like which marketing channels resulted in higher conversion rates which category of customers were likely to invest in our products.
The analysis helped in changing the marketing strategies of the company and resulted in higher conversion ratios.
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I later moved to IBM where I continued working as a Data Analyst.
I gained a thorough understanding of relational databases and ERP systems.
My work at IBM included, creating database tables, setting data validation & quality control checks, data cleaning (identifying anomalies or outliers, data validation, fill missing values), performing Exploratory data analysis, generating interactive reports by accessing multiple database tables, manipulating data according to the business requirements, Presenting the insights from the EDA and reports.
Developed programs to import and export data in and out of the ERP system.
Developing programs or rather analytical approaches for the optimization of inventory and optimization of trucks used for transportation of CPGs.
Development of Tableau dashboards to visualize the performance of different products.
Worked on machine learning techniques like Linear Regression, Logistic Regression, Random Forest & Time Series Forecasting.
I was also a dedicated and single point of contact resource for the APO (Advanced Planning & Optimization system) when I was working with my client Unilever.
Developed a logistic regression model to predict a person’s inclination to avail a particular loan product. The model yielded an accuracy of 78.67%.
Completed a senior level project for an insurance company to classify the churn rate of the life insurance policy holder and the potential customers list were given to underwriters to optimize the premiums accordingly. As a result, churn rate was decreased by 12%.
Effort & Complexity Prediction: Used Linear Regression to analyze the data obtained from Magic (A tool which contains details of the work orders / issues assigned to our team at IBM) to predict the number of hours required for completion of work orders and the complexity of the work order.
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Worked as a Data Science Student consultant for Milacron.
Built ARIMA and Croston models for forecasting demand. We used two different approaches for forecasting depending on the pattern in the historic sales data. Developed an analytical approach to optimize inventory levels of replacement parts in order to maximize customer service levels and drive company growth. The forecasting model that we developed resulted in an increase of 44% in forecast accuracy. The client was also very happy with the approach that we developed for the inventory model.
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Some of the other Analytics projects that I have carried out on my own include:
Risk Analysis of German Credit Data: Used German Credit data to analyze the performance of Logistic Regression, Random Forest and Boosting in predicting the applicants as Good credit risk & Bad credit risk. Achieved an AUC of 0.85 for Boosting.
NLP & Sentiment Analysis of reviews on Yelp.com: Identified the key attributes that influence customer ratings from a restaurant perspective. Performed Sentiment Analysis to identify words that contribute to positive and negative sentiments and analyzed the general emotions expressed across different ratings.
Text Mining & Sentiment Analysis of reviews on Glassdoor. Analyzed the reviews given by employees of companies Google, Facebook, Amazon and Netflix to identify the most commonly spoken topics and issues in reviews. Identified the key attributes that influence the ratings given by employees. Identified the words that contribute to positive and negative sentiments and analyzed variations in the emotions expressed in the reviews over the years.
Analysis of FAA dataset to predict landing Distance: Studied the factors that impact the landing distance of a commercial flight and built a Linear Regression model to predict the risk of overrun.
Exploratory Data Analysis on Transaction Data: EDA on Carbo-Loading dataset that contains household level transactions. The study helped in understanding the performance, marketing strategies and interaction between different brands and products to provide coupons/product recommendations to the customers.
\(~\) o I am working on the next phase of this project. To use Association rules and Market basket analysis on transaction data to determine which products are frequently bought together. The analysis could help in determining which products can be grouped together on Aisles, Promotional discounts or offers can be provided on one of the products that are frequently bought together.
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SKILLS & CERTIFICATIONS:
Software and Programming: R, SAS, Python, SQL, Tableau, VBA/Macros, MS Excel & SAP ABAP
Statistical/Business Skills: Machine Learning: Linear regression, Logistic regression, Decision trees, Random forest, A/B testing, Clustering, Association Rules, Time series forecasting, Inventory Management, Data Visualization, Text mining, Natural Language Processing and Sentiment analysis
Courses/Certifications: Analytics 360 from ATI India, Data Scientist with R on datacamp
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HONORS & ACTIVITIES:
Single handedly implemented one of the most complex projects viz “Amazon Pantry Project” for Hindustan Unilever
Received award for the implementation of GST project, which was the most prestigious & complex project post SAP implementation at Hindustan Unilever
Deep skill award for learning and working on the latest Data Analysis techniques.
Additionally, I received several client appreciations for successfully identifying several complex scenarios and implementing quick problem-solving techniques through my approach strategy.
Oranizing Team member of Let’s do it! Mysore: In the course of developing my technical skillset, I also involved myself in extracurricular and social activities. I was a part of the organizing team of Let’s do it! Mysore, a non-profit organization, whose main focus was to spread awareness on the importance of maintaining cleanliness, proper disposal and recycling of household garbage. I headed a group of 150 members in a mass cleaning drive organized by Let’s do it! Mysore where more than 2500 members participated. Our work with the NGO led to Mysore being declared as India’s cleanest city three years in a row.
Volunteer for Project ReachOut: I involved myself with Project ReachOut, an initiative focused on the teaching activities at government schools and assisting mentally challenged kids with education programs. Involvement in such activities has helped me stay connected to society and enriched my sense of being whilst underlining my overall sense of purpose towards helping others in their times of need.
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CONTACT & LINKS: