Jul 2024 – Sep 2025 · 1 yr 2 mos · Paris, Île-de-France, France

• I pursued a Master of Science in Computer Science with a specialization in Data Science and Analysis at EPITA Paris. The program equipped me with advanced knowledge and practical skills in data analysis, machine learning, and big data technologies. Through this specialization, I developed expertise in handling complex datasets, building predictive models, and leveraging data-driven insights to solve real-world problems.

Jan 2024 – Jul 2024 · 6 mos · Bengaluru, Karnataka, India · Hybrid

• As Trainee Decision Scientist-3, I worked on data engineering solution and managing 1500+ data assets which are being consumed by down-stream users for reporting and insight generation for one of the leading USA Retail giant.
• Data Engineer Lead:
• 1. Team lead overseeing daily ETL processes and maintaining the availability of over 1500+ Hive assets.
• 2. Monitor and manage 40+ Azure Data Factory pipelines, promptly addressing any failures.
• 3. Ensure timely availability of data by coordinating with upstream vendors (source teams) if data is delayed at the source end.
• 4. Address data discrepancy issues raised by product POs and POCs, ensuring data integrity and accuracy.
• 5. Collaborate on enhancing existing pipeline structures and implementing new enhancements proposed by POs and POCs.
• 6. Maintain continuous improvement efforts to optimize ETL processes and overall data management efficiency.

Oct 2022 – Jan 2024 · 1 yr 3 mos · Bengaluru, Karnataka, India · Hybrid

• As Trainee Decision Scientist-2, I worked on data-driven decision-making processes and utilizing various analytical tools and techniques to provide insights and solutions to one of the leading US Retail giant.
• I have worked on 4 different engagements:
• 1. Data Engine DevOps and Support - Worked on managing ETL processes which are responsible for daily data asset refresh to ensure on time data availability. Also solved various data discrepancies issues raised by POs and POCs of the reporting layer.
• 2. Hash Value Recalibration - Worked on a data escalation where historical data sets were corrupted due to backfilling the past data without considering Upsert logic implementation. We have recalibrated the 150+ data asset in 2 phase, where phase 1 was dedicated to fix the dates for all the records and phase 2 was dedicated to fix the has value and remove duplicates created while backfilling.
• 3. Neo4j Graph Analytics POC - Worked on a graph analytics proof of concept where we used Neo4j Database as our tool to derive quick and valuable relationships between various pet diseases and related parameters. The final report was using a React web app interface to find the relationship between various parameters.
• 4. CSL SSP - Worked on a detailed analysis report titled SSP(Solving Specific Problem) where we analyzed the root causes behind declining customer satisfaction level for one of the largest buyers for our clients. We analyzed various trends from past data and drew insights to deliver the actionable conclusion.

Aug 2021 – Sep 2022 · 1 yr 1 mo · Bengaluru, Karnataka, India · Hybrid

• As an Assistant System Engineer at Tata Consultancy Services in Bangalore, I had the opportunity to work with a prestigious European Energy Organization, where I focused on IT Service Management. During my tenure, I was able to demonstrate my proficiency in ServiceNow by clearing the CSA certification exam.
• My responsibilities included handling various aspects of ServiceNow, such as lists, forms, filters, incident management, change management, request management, report management, knowledge management, service catalog, flow designer, workflow, scripting, notification, import set, transform maps, plugins, and other related configuration and development activities.
• Through my work, I gained valuable experience in managing IT services for a large organization and developed my skills in ServiceNow administration and development. Overall, my experience at Tata Consultancy Services has provided me with a strong foundation in IT Service Management and a deep understanding of ServiceNow.

Jul 2020 – Aug 2020 · 1 mo · Bengaluru, Karnataka, India

• During my internship, I focused on customer segmentation using the K Means Clustering algorithm to achieve desired outcomes. Through this project, I gained hands-on experience in applying machine learning techniques to real-world data and developing solutions to business problems. I was able to analyze large datasets, identify patterns, and group customers into distinct segments based on their behavior and characteristics. By implementing K Means Clustering, I was able to effectively target specific customer groups and personalize marketing strategies, leading to improved customer satisfaction and business performance.
• Overall, this internship allowed me to gain practical knowledge in data analysis and machine learning, enhancing my skillset for future opportunities.

Jun 2020 – Aug 2020 · 2 mos · India

• The program I participated in was a 9-week long endeavor, which included 7 weeks of training and 2 weeks dedicated to project work. During the course of the program, I completed 2 mini-projects and 1 major project.
• The program provided me with the opportunity to gain practical experience in my field of study and allowed me to apply the knowledge I had acquired in a real-world setting. Through the mini-projects and major project, I was able to demonstrate my ability to solve problems, work effectively in a team, and meet project deadlines. Overall, the program was a valuable learning experience that helped me develop my skills and prepare for my future career.

Jul 2019 – Aug 2019 · 1 mo · India

• I completed a 2-month internship focused on machine learning, which was supported by the Microsoft Technology Associate Program. During this internship, I gained hands-on experience with various machine learning techniques and tools. I worked on several projects, including developing predictive models, building natural language processing models, and using deep learning algorithms for image recognition tasks.
• The program provided me with a comprehensive understanding of the various aspects of machine learning, including data preprocessing, model selection, and evaluation. This experience was invaluable in helping me develop my skills and knowledge in the field of machine learning.