Jan 2025 – Feb 2025 · 1 mo · Gurugram, Haryana, India · On-site

• Applied stochastic calculus and time-series models (e.g., GARCH, ARIMA) to analyze and forecast the volatility of financial assets, creating predictive tools to enhance quantitative risk management frameworks for banking clients.
• Developed and implemented optimization algorithms based on Modern Portfolio Theory, utilizing linear algebra and Monte Carlo simulations in Python to construct efficient frontiers for asset allocation strategies.

Jun 2024 – Aug 2024 · 2 mos · Gurugram, Haryana, India · On-site

• Developed and maintained Azure DevOps pipelines for continuous integration and deployment, employing YAML coding and ARM templates to automate software delivery processes and ensure efficient project management and collaboration; Automated repetitive tasks and workflows using Node.js scripting, significantly improving operational efficiency and reducing manual effort.
• Managed Kubernetes clusters to orchestrate containerized applications, optimizing deployment strategies and scaling microservices for enhanced performance and scalability; Implemented microservices architecture for modular and scalable application development, leveraging Docker and Kubernetes to achieve agile and resilient software solutions; Designed and implemented infrastructure as code using Terraform, enabling consistent provisioning and management of cloud resources across multiple environments.
• Conducted comprehensive Playwright user testing to validate application functionalities and detect potential issues, ensuring robust software performance and user experience; Led high-risk testing initiatives to evaluate system resilience and performance under extreme conditions, identifying vulnerabilities and implementing mitigation strategies to safeguard critical applications.

Apr 2024 – Jun 2024 · 2 mos · Remote

• Developed a real-time automated ML model for sentiment analysis of tweets; Utilized Natural Language Processing (NLP)
• techniques and classifiers such as Logistic Regression, Bernoulli Naive Bayes, and Support Vector Machine (SVM); Analyzed
• tweet sentiments to classify them as positive, negative, or neutral, aiding brands in understanding customer opinions, market trends,
• and competitor strategies.
• Conducted Exploratory Data Analysis (EDA) using Python to understand the dataset's structure and key statistics; Created
• visualizations in Power BI and Tableau to identify patterns, correlations, and trends within the Iris dataset; Documented
• methodologies and provided detailed explanations for identified patterns and insights.
• Cleaned and preprocessed a weather dataset using Python, addressing missing values and outliers; Performed advanced data analysis
• and created interactive dashboards in Power BI and Tableau to highlight trends and correlations in weather parameters; Implemented
• correlation and regression analysis to predict weather parameters and documented the insights derived from the analysis.

Apr 2024 – May 2024 · 1 mo · London Area, United Kingdom · Remote

• Engineered behavioral segmentation algorithms via statistical clustering on high-dimensional alternative datasets, utilizing LLM APIs (OpenAI) to parse and structure unstructured text reviews; processed 1 million+ historical data points to extract 43 distinct predictive purchasing signals for quantitative trend forecasting
• Modeled cross-sectional market share and competitive pricing matrices to identify statistical anomalies across a $2M retail sector; architected automated Tableau/Power BI ETL pipelines to synthesize multi-source, high-noise data, reducing strategic reporting latency by 2% and saving 3 hours/week

Mar 2024 – Apr 2024 · 1 mo · Remote

• Identified key factors contributing to customer churn and developed a predictive model to help the company retain customers; Achieved an accuracy of over 85% in predicting customer churn; Proposed strategies that could potentially reduce churn by 15%.
• Developed an image classification model to detect common plant diseases from images of plant leaves, aiding farmers in managing crop health; Achieved an accuracy of over 90% in classifying plant diseases; Identified the top three types of plant diseases the model could accurately detect.
• Built a robust fraud detection system using ML to identify and prevent fraudulent credit card transactions; Achieved precision and recall scores above 90% in the fraud detection model; Developed a real-time fraud detection system with low latency.

Nov 2022 – May 2023 · 6 mos · New Delhi, Delhi, India · Remote

• Conducted in-depth market research to analyze industry trends, consumer preferences, and competitive landscapes, providing valuable insights to inform strategic decision-making.
• Developed and executed targeted marketing campaigns aimed at increasing brand awareness and engagement, resulting in a notable 10% expansion of the company's reach within the identified market segments.
• Utilized analytical tools and metrics to track campaign performance and effectiveness, facilitating data-driven adjustments and continuous improvement efforts.

May 2020 – Dec 2020 · 7 mos · Delhi, India · Hybrid

• Spearheaded social media campaigns and outreach initiatives as part of a U.S. Embassy-led initiative aimed at promoting lung health awareness.
• Conducted weekly research on the correlation between air pollution and asthma, contributing valuable environmental data research to the foundation's initiatives.
• Collaborated with a team to compile and analyze environmental data, identifying trends and correlations to inform public health strategies and advocacy efforts.
• Interviewed key stakeholders including Dr. Rajiv Shukla and U.S. Embassy executives, facilitating insightful discussions and enhancing project visibility.
• Recognized for outstanding contributions, receiving a Letter of Recommendation from the U.S. Embassy, and achieving selection from a competitive pool of 290 students

Jan 2020 – May 2020 · 4 mos · Gurugram, Haryana, India · Remote

• Participated in a 3-month mentorship program with Niti Aayog under the Atal Innovation Mission, gaining exposure to innovation and entrepreneurship under a prestigious government initiative.
• Achieved recognition as part of a top 20 team globally in a competitive competition, showcasing problem-solving abilities and innovative thinking on an international stage.
• Engaged in immersive design and data workshops, refining skills in data analysis and visualization to effectively communicate insights and drive decision-making.
• Gained hands-on experience in artificial intelligence (AI) and machine learning (ML) modeling through Adobe AI projects, applying algorithmic techniques to solve real-world problems.
• Received comprehensive training in algorithms and coding, honing proficiency in fundamental computational concepts and programming languages to support AI and ML initiatives.