Rohan Gala Email & Phone Number

Jersey City, NJ, US

London, GB

• Built a framework to carry out the Replay process of more than a billion trades for the Trades and Transaction Report Operations Team.
• Handled and reconciled the replay process of more than 300 million FCA trades and 50 million CBI Trades across 30 TB worth of data.
• Coordinated with cross-functional teams and transitioned 142 Microsoft SSRS reports to Tableau in a streamlined manner.
• Developed a library and invoked python in the team to automate big data tasks like text parsing, data manipulation, regex ops, etc.
• Automated the flow in python to parse multithreaded logs, extract key metrics, generate a presentation and mail it on a schedule, along with streaming the data to Tableau. Along with following the trend, it helped the.
• Assisted in setting up the plan of action to migrate the on-premise data warehouse to AWS.

Newark, NJ, US

• Automated PO generation flow for 2000 vendors in python, reducing the processing time by 99%, eliminating human effort and error.
• Built a scraping tool to extract the lowest prices and the reviews of the product to get rid of any fraud or breaching of policies.

Newark, NJ, US

• Integrated the data from multiple sources on PowerBI with a structured model and developed data visualizations, reports, dashboards, and analyses in PowerBI to distribute data insights in an easily digestible manner to.
• Supported the PIDSA US team to implement and deploy an ML model that predicted the top 20 products present in the market but new to Panasonic. Helped in explaining the business logic and the benefits of the project to.

New York, NY, US

• Perform data wrangling on company’s marketing messages to client. Developing a dashboard after performing NLP on the clean Data to gain insights such as: phrases that trigger higher engagement rates, category of.
• Transforming vast data sets from syndicated research tools (Nielsen, GFK MRI) into compelling actionable insights and deriving key takeaways. Reporting directly to the manager for implementing the resulting strategies.
• Predicting the probability of Client finalizing a deal to forecast the sponsorship amount by the client for an event.
• Develop SQL Queries to extract revenue data from CRM for last 3 years. Visualized the time series data in tableau to get insights.

Zurich, CH

• Goal: Predict the next three wealth management branch locations for UBS. (Given data: Present 330 locations of UBS WM Branches)
• Collected Data related to the High Net Worth Individuals (HNWI) and WMAs, cleaned them using “City,State” as the Unique Key.
• Clustered the data based on Average Zillow Home Value (AZHV) and Political Donations and labeled the cities in a cluster with low AZHV and Low Political Donations as 0 and the 330 cities with UBS Branches as 1. Hence.
• Used Data Ensemble modeling by applying machine learning algorithms like Naïve Bayes, Decision Tree, Logistic Regression Neural networks and Support Vector Machine (SVM). Selected the cities for which all the.
• Completely automated the project by building a website using python and embedding a dashboard to take weights as the input and give the final three cities as the output.

Dallas, TX, US

• Software Developer and Data Analyst at Global Customer Service of AT&T Global Business Services India Pvt. Ltd.
• Built a tool to automate the network changes carried out by AT&T on client sites after performing necessary stakeholder analysis.
• Developed the tool using python code by applying Object Oriented Programming and Software Development Life Cycle concepts.
• Led the UI/UX development of the software and designed the entire layout of the software using PySide and PyQt.
• Worked closely with System Engineers to develop a workflow consisting frequently used features to enhance the user-interface.
• Used VBA to autogenerate reports post-change to monitor entities like time taken, steps involved, parameters changed, etc.

• Responsible for the functioning and building a timeline of 3 YouTube channels to grow the subscribers of the channels.
• Performed a sentimental analysis by scraping the comments of the videos to gain an insight into the user demands and reviews.
• Designed a ML model that suggests tags using data from Google Analytics to increase the SEO score of a video.
• Helped the channel cross 100,000 views in a span of 2 months using creative marketing strategies, within half the allotted budget.
• Built a database using MS Access to maintain the videos with entities like views, duration, keywords, etc. helping the company consolidate the entire data which earlier resided in Excel.

Master Of Science - Ms, Business Intelligence And Analytics (Data Science Concentration)

Bachelor Of Engineering - Be, Electronics