Aditya

E:-M:- Aditya Aranya (https://www.linkedin.com/in/aranyaa/) (https://adityaaranya.co/) Data Analyst / Visualisation / Business Intelligence / Data Science Graduate Excel, SQL, Tableau, Power BI, MongoDB, Python Education & Qualifications ✓ Master of Information Technology, Data Analytics, 2019, University of Technology Sydney, Australia ▪ ▪ ▪ ▪ ▪ ▪ ▪ ▪ Fundamentals of Data Analytics Advance Data Analysis & Algorithms Business Intelligence Deep learning & convolutional neural networks Data Warehousing Data Visualization & Visual Analytics Project Management Advanced Project Management ✓ Bachelor of Computer Science, 2016 ▪ ▪ ▪ ▪ ▪ ▪ ▪ Object-oriented programming Cloud Computing Microprocessor Architecture Software Engineering Natural Language Processing Data Mining Data Structures & Problem Solving Certifications ✓ Python Programmer Track for Data Science, DataCamp (2018) ✓ Logic and Computational Thinking, EDX (2018) ✓ Intermediate SQL, SQLBolt (2019) Key Skills ✓ Programming: Python, C, C++, HTML, JavaScript, DAX ✓ Database Systems: MySQL, MongoDB (NoSQL) ✓ Frameworks: Scikit, Pandas, NumPy, PyCharm, Seaborn, TensorFlow, Keras, Git ✓ IDEs: Jupyter Notebook/lab, PowerBI, Tableau, Google Collab Work Experience Junior Business Intelligence Consultant – Sydney Metro & CPB Contractors + UGL contracted by FinXL IT Solutions January 2020 – May 2020 • Work independently or as a part of the team to design and develop analytics/reporting solutions using SQL, Python and Power BI. • Developed an automated workflow approval process from Procurement Officers to Project Directors using Microsoft PowerApps for RFT and RFA to streamline the process. • Worked directly under Project Director, Commercial director and Procurement Manager for effective analysis and business development activities. • Provided recommendation for optimisation, automation and standardization of BI solutions. • Developed ten dashboards for ten streams of Procurement using KPI for individual streams and setting up a granular aspect for each individual dashboard. E:-M:- Retail (Permanent Part-time) – Vanitas Pty Ltd Sydney, Australia September 2017-November 2019 • Provided excellent customer service to customers of established retail business by being the front face and address customer issues with quick response time. • Worked twenty hours per week, further maintaining a perfect attendance record. QA Test Engineer – Codemasters Ltd. Pune, India March 2017- June 2017 • Identification of bugs/flaws in the system provided developer teams with detailed reports and recommended fixes. • Jira, Software Development Lifecycle. Process Associate – Global E-Procure. Mumbai, India September 2016-February 2016 • Worked in coordination with finance giants Prudential Ltd. • Carried out market intelligence and CRM reports to help key stakeholders make decisions based on essential attributes identifying drivers of price that are directly influential to vendor performance. • Procurement Lifecycle. Projects Analysis of Cell phone Data with PowerBI: Machine learning with PowerBI for predictive analysis of selfcellphone provider bills over seven months. • Used PowerBI for data cleaning, manipulation, and querying with DAX programming language to perform dynamic aggregation. • Achieved HD grade for the project, predicted cellphone usage for the first ten days of August with an average of 12.21 calls. Development of an interactive tool to monitor drug consumption through the analysis of used syringes: Data analysis and visualization project in collaboration with the European Monitoring Centre for Drugs and Drug Addiction (EMCDDA). • Implemented monitoring tool to analyze drug consumption in multiple locations of Europe. • Combining multiple workbooks in various formats from multiple sources to a single streamlined source of data was the main challenge. Numerous redundancies present in the data were efficiently managed without stripping the data and using it to our advantage by managing stakeholders weekly. • Used D3.js and Leaflet.js library to build interactive visualization using streamlined data to understand the maximum consumption of drug types across the map of Europe. • Achieved HD grade. Deep Learning on License plate detection • Derived the best-suited algorithm concerning time and space complexity by using object detection algorithms VGG16 and FasterRCNN. • Phase 1: Detect the vehicle and its appropriate license plate. • Phase 2: Detect the characters on the number plate by building a second dataset to train the model for numbers and alphabets followed by a sorting algorithm. • Achieved runners-up with more than 20 groups in the competition. • Acquired HD grade for the project. BI Solution with Tableau: Analyzed data of Flight delays with the help of synthetic data. • Provided synthetic data by adjusting parameters such as weather delay time, categorizing the max delay for each specified weather type. Addition of multiple types of delays not included in the dataset. • Differentiated source and destination delays and efficiently merged with the source data. • Built a dashboard to analyze and visualize the delays in flight, understanding various attributes concerning synthetic data. E:-M:- IBM Telco Customer Churn: Machine learning project to predict the number of customers churned. • Used supervised learning algorithms such as K Nearest Neighbor, Naïve Bayes, Logistic Regression. Further optimized best candidate model by model performing matrices such as comparison, confusion matrices, ROC curve. • The final model predicted whether a customer would churn in the future with 75.89% accuracy. Predict Visa Status of Employees: Machine learning project/In-Class Kaggle competition to predict the visa status of employees across the US Department of Labor. • Used supervised learning algorithms such as Decision Tree, Random Forest, Gradient Boosted Trees by various parameters such as bagging, boosting, etc. • The final classification model predicted if the applicant will get into the US or not with an accuracy of 79.363%. GovHack Australia 2019 • Participated in GovHack Sydney sponsored by Infosys and AWS. • Documented a template scalable to analyse the job market and future trends in regional Australia based on the opensource government datasets for employment purposes. • After implementation, the final model can predict employment for an individual based on education, age, region, and how likely will the location favor to get a job, further recommending the best region to increase job prospects. Publications Effective bug triage using a cold-start recommendation system • Automated bug triage system dealing with the cold start with the help of feature selection and instance selection in a predictive environment to increase the accuracy of the model. • Analyzed the use of Naïve Bayesian Classifier efficiency with regards to computational complexity. • Accomplished HD grade for the project, published research paper in the International Journal of Computer Science and Engineering. Extra-Curricular Activities ✓ ✓ ✓ ✓ Member of the Statistical Society of Australia. Participated in the “EVER-GREEN” program, an initiative to clean plastic pollution drivers. Contributed in Fund-Raising initiative organized by “HELP AGE” to support elderly homeless people. Succeeded 3rd rank in High School in “NATIONAL CYBER OLYMPIAD” conducted across the globe for cyber aptitude. ✓ Participated in “Techunt 2013”, a three-day workshop organized by CSI focusing on entrepreneurship in the global market. ✓ Played as a state and national level football player Contact Details Email:-Mobile:- References Available upon request