Akshay Saini

AKSHAY Home: New Delhi, IN SAINI 📞 - ✉- OVERVIEW I am a young professional who is a graduate in Computer Science Engineering with passion for data analysis, looking to gain more experience in the field of data analytics. WORK EXPERIENCE • Associate Analyst EDUCATION • Galaxian Technologies LLP | Jul 2019- Jan 2020 - • B.Tech (Computer Science and Engineering) I joined Amity University, Noida for a bachelor’s in technology under the computer science stream (201317). My knowledge of the IT and Computer Science led me to join Wipro and then later IBM in a short span of time. Product related analytical work using R. Service Delivery Specialist IBM India Pvt. Ltd | Jan 2018- May 2019 Jaguar Land Rover: - Analyzed critical data and interacted with different teams of the project at various locations to reduce the failures of job files by 30%. • Finished my schooling from Apeejay School, Pitampura, Delhi. Manitoba Telecom Services: - • Aggregated data from tables to form a much better view of the data. Project Engineer Wipro Technologies | Sept 2017- Dec 2017 - 12th BOARDS CBSE | May 2012 • 10th BOARDS CBSE | May 2010 Received first senior secondary certificate while studying in Apeejay School, Pitampura, Delhi Worked with .Net technology using C#. PROJECTS INTERNSHIPS • •. Galaxian Technologies LLP, Delhi | 2019 Blazing FootStats: Football Players Analysis AT&T | May 2016 - - Part of the summer internship, part of a solo project. It was the analysis of 100+ football players and out of that the top 11 players were found out by analyzing their statistical performance. The twitter popularity was also found out of 4 players of each playing position. Python, Hadoop and Tableau platforms were used. Smart Mirror - • Headed this analytical side of the project for product – Smart Mirror. It included the analysis of the possible market size and the cost to put it into production. Mainframe Analysis IBM, Noida/Gurgaon | 2018 - Part of the team which handled multiple accounts. PERSONALITY SKILLS - • JLR and MTS were our two clientele which were handled by our team where we were given mainframe data by the client and we diagnosed the possible area to improve the efficiency of their transaction using IBM’s analytical tools. • • • Stock Market Analysis Using Clustering and Machine Learning Algorithms • Amity University, Noida | 2017 • - It was a solo technical (analytical) project. It included the clustering of 300 stocks based on the performance and predictive machine learning models used to predict the value of the stocks in the coming future. ADDITIONAL ACTIVITIES • • • RESEARCH PAPER • • • Possess strong communication skills, both spoken and written, very good with client engagement Attentive to details, accurate and a keen observer Excellent team working skills, good organizational and social skills Patient and well organized, ability to work well under pressure. Easily adaptable to new environment. Participated in organizing various IET events in Amity University, Noida. High school football player. (Various awards won). Participated and won in various Extempore, Speech and Quiz Competitions at High School Level. Successful participation in National Math Olympiad. Clustering Based Stock Market Analysis (2017). - The paper surveys different approaches of clustering and presents a much better way to apply clustering to stock prices. Applying clustering before using predictive algorithms gives us a better result than just using them directly. The research paper is accepted and submitted to “2nd International Conference on Recent Innovations in Computer Science and Information Technology (RICSIT-2017), hosted at University Institute of Information and Technology, Shimla and selected to be published by IJCTA (International Journal of Control Theory and Applications). LINGUISTIC SKILLS - TECHNICAL SKILLS • • • • PROGRAMMING LANGUAGES – C++, C#, Python, R DATABASES - SQL, Hive OPERATING SYSTEMS – Windows, UNIX MISCELLENIOUS SOFTWARES – MS Office, MS Excel, Hadoop, Mainframes, Tableau • • Proficient in speaking English and Hindi. Comfortable with entry level German.