Jul 2024 – Dec 2024 · 5 mos · India

• Served as an RLHF (Reinforcement Learning with Human Feedback) specialist for Scale AI via SoulAI, training Google’s Gemini and OpenAI’s ChatGPT. Focused on analyzing model outputs, identifying inaccuracies, and refining responses to enhance performance and ensure high-quality results, primarily in coding (Python, SQL) and statistical problem-solving.

Apr 2024 – Jul 2024 · 3 mos

• Tools Used: AWS Sagemaker, AWS Athena, AWS S3, Quicksight
• Programming languages used: Python(Numpy, Pandas, Matplotlib, Sklearn, Pythena, Boto3)
• Single-handedly led the entire data science process from data loading to model deployment for company’s hiring solutions data science tool ‘Decision Point’.
• Identified target metrics for ‘Decision Point’ predictions, specifically tailored for hourly jobs in the US market.
• Extracted data using SQLite in AWS Athena, performed exploratory data analysis, and engineered variables using AWS Sagemaker in Jupyter. Analyzed data with Amazon QuickSight. Utilized AutoML in AWS Sagemaker for model building and managed deployment via AWS S3 bucket.
• Managed data and built models for various clients from different industries like automotive after-market, fast food industry etc.
• Documented all variables, model workings, and performance metrics for each hiring position and client.
• Worked directly with the US team, providing guidance on requirements from the client and data needs while ensuring regular progress updates.
• Collaborated with the Director of Data Science, data engineers, and analysts to facilitate project completion. Engaged the entire tech team in understanding data science processes for future project collaboration, by giving them in depth knowledge of process and guiding them with the courses for better understanding of the field.

Apr 2023 – Apr 2024 · 1 yr · Bengaluru · Remote

• Ensured integrity and security of Swiggy's Instamart Grocery Delivery product by focusing on customer fraud prevention.
• Developed and implemented strategies to track, analyze, and mitigate fraud incidents, resulting in enhanced trust and reliability of the platform.
• Created dynamic dashboards to monitor weekly cancellation numbers, gratification levels, and delivery fraud incidents, providing actionable insights to relevant teams.
• Implemented rules within the platform to detect and prevent delivery executive frauds, significantly reducing fraudulent activities and cancellations.
• Utilized SQL, Python, Google Sheets, and Excel to extract, analyze, and present data-driven insights, enabling data-informed decision-making.
• Collaborated closely with cross-functional teams, including product managers, data analysts, and technical experts, to drive comprehensive fraud prevention strategies.
• Acted as a subject matter expert, providing guidance and mentorship to colleagues, fostering a culture of continuous improvement and knowledge sharing.
• Proactively stayed updated with emerging fraud prevention trends and technologies, ensuring the application of cutting-edge practices.
• Presented work and findings to higher stakeholders, including General Managers and VPs, effectively communicating the impact of fraud prevention measures and driving support for further initiatives.

Aug 2022 – Mar 2023 · 7 mos · Greater Bengaluru Area

Apr 2022 – Jul 2022 · 3 mos · Gurugram, Haryana, India

• As a part of Revenue team, work included:
• 1. Extracting data from Databases of the company, as per requirement of the Stakeholder using SQL or R Programming and making reports based on that using R programming, Python and Google Sheets/Excel.
• 2. Doing analysis of the data, finding the hidden anomalies in the data and suggesting the next steps to be taken.
• 3. Create data dashboards for stakeholders to have regular visibility on key metrics, who report directly to the CEO and CXO of the company.

May 2021 – Apr 2022 · 11 mos · Noida, Uttar Pradesh, India

• 1. Designed RPA for creating training report for HR department and for external clients, using Automation Anywhere and Power BI.
• 2. Created POC for complaint management system (ticketing system), for client, using Automation Anywhere.
• 3. Created POC for extracting data from invoices using IDP(Intelligent Document Processing) tools and logged that data to companies invoice management platform, then generated a report for the same, using IQ bot, Bot Insights and Automation Anywhere.
• 4. Developed expense reimbursements management for HR department, using Automation Anywhere .
• 5. Automating Azure virtual machine starting and stopping based on the email sent by the admin to registered email, using Azure and Automation Anywhere.
• 6. Self Project: Developed charts and performed EDA of data, based on the CSV file entered by user, using Automation Anywhere and Python.

Mar 2021 – Apr 2022 · 1 yr 1 mo · Delhi, India

• Here, I have to upload answers of the questions asked by students from various countries, based on computer science, statistics and Data science

Nov 2020 – Dec 2020 · 1 mo

• 1. Prediction of marks scored by a student based on the number of hours studied. Applied Simple Linear Regression using Python to predict.
• 2. Predicted the optimum number of clusters for sample data of eyes (Iris) dataset. Applied K-means cluster in Python to predict.
• 3. Exploratory Data analysis on retail data using Python.

Sep 2020 – Nov 2020 · 2 mos

• In this internship, I learned about communication, body language and how to act in different situations of corporate culture. Also worked on oratory skills.

Dec 2019 – Jan 2020 · 1 mo · Gurugram, Haryana, India

• Learned about sales and marketing and how to use various iOS products.