Kushal Adity

Data Scientist

Irving, Texas, United States6 yrs 9 mos experience

Highly StableAI Enabled

Key Highlights

Proven track record in machine learning model implementation.
Expertise in data analysis driving business impact.
Strong experience in end-to-end machine learning pipelines.

Stackforce AI infers this person is a Data Scientist with expertise in AI and Machine Learning across various industries.

Contact

kushaladity@gmail.com LinkedIn

Skills

Core Skills

Machine LearningData AnalysisData Visualization

Other Skills

ARIMAAmazon Web Services (AWS)Artificial Neural NetworksAzure Cosmos DBAzure DevOpsAzure Synapse AnalyticsBig DataCConvolutional Neural Networks (CNN)Data IntegrationData MiningData ModelingFAISSFraud DetectionGenerative AI

About

Dependable and goal-oriented Data Scientist with 5+ years of experience in Quantitative and Qualitative Data Analysis. 5+ years of experience applying Python, R, SQL, SAS, Spark for Data Analysis, Machine Learning, Data Modeling, and Data Visualization. 5+ years of machine learning/data Science experience with a proven track record of developing and implementing large scale algorithms that have significantly impacted business revenues and user experience. Expert level proficiency with MS Office suite, Spreadsheets and Databases. 1. I am fluent in Data Science and Machine Learning tools - Python, R, SQL, Excel, PowerBI, Tableau as well as different Machine Learning and Deep Learning frameworks like Pandas, Scikit-Learn, NumPy, SciPy 2. Experience with different methodologies: Machine Learning - Regression, Decision Trees, KNN, K-means, Random Forest, XG Boost 3. Experienced in building end-to-end Machine Learning pipelines from Data Ingestion till Deployment 4. Adept at transforming results from hypothesis testing, and machine learning to tangible business impact 5. Aptitude and zeal to drive effective communications to gather requirements and drive impact

Experience

Microsoft

Data Scientist (via Centific)

Jun 2024 – Present · 1 yr 9 mos · United States · Remote

Designed and implemented multi agent orchestration systems enabling specialised AI agents to collaborate seamlessly delivering more complex, autonomous workflows.
Built a multi‑agent, multi‑model incident review automation system combining LLM reasoning, reviewer arbitration, and structured reporting to reduce manual DRI workload while preserving auditability and decision quality.
Enhanced and fine-tuned fraud detection anomaly models by incorporating updated fraud scoring techniques and implementing time-series forecasting to proactively identify emerging fraud patterns.
Achieved a boost in the efficiency of machine learning-driven anomaly detection by optimizing Prophet model parameters and strategically utilizing available fraud scores.
Led end-to-end deployment of fraud detection models through automated CI/CD pipelines using Azure DevOps, ensuring smooth and reliable migration from development to production.
Leveraged Azure Synapse Analytics and Azure Cosmos DB to manage and analyze large-scale data, providing critical insights to inform model training and refinement. Utilized Visual Studio and Visual Studio Code to accelerate model development cycles through efficient coding, debugging, and iterative testing.

Azure DevOpsAzure Synapse AnalyticsAzure Cosmos DBPythonMachine LearningFraud Detection+1

University of illinois at chicago - graduate college

Graduate Teaching Assistant

Jan 2023 – May 2024 · 1 yr 4 mos · Chicago, Illinois, United States · On-site

Aids Operations Management course by taking technical lab sessions, preparing and grading assignments for students, and meet students for doubt clarifications

Amazon

Senior Risk Analyst

Aug 2021 – Dec 2022 · 1 yr 4 mos · Bengaluru, Karnataka, India

Implemented Fraud Detection System: Developed a statistical and ML model to identify fraudulent transactions; Prioritized results for on-ground investigations
Business Process Optimization: Formalized and executed the fraud detection process using analytics and machine learning, resulting in savings of partner reimbursements
Fraudulent Seller Identification: Leveraged statistical methods model to predict the likelihood of Amazon's selling partners engaging in abusive behavior
Data Integration and Dashboard Development: Collected and merged data from multiple structured and unstructured sources using PySpark. Built dashboards that improved business reporting processes, aiding facility centers in tracking 20+ crucial Key Performance Indicators (KPIs) for efficient monitoring

Machine LearningData AnalysisFraud DetectionStatistical AnalysisPySpark

Tredence inc.

2 roles

Senior Business Analyst

Promoted

Jun 2019 – Aug 2021 · 2 yrs 2 mos

Revenue Optimization: Designed and implemented an ML model in R utilizing the K-Means clustering algorithm for a leading industrial client. Identified potential revenue loss due to the client's pricing strategy and rectified the pricing grid
Time-Series Forecasting: Developed Time-Series forecasting models using ARIMA and Heuristic methods to accurately predict the company’s total footfall, activations, penetrations, and revenue
Data Integration and Analytics: Assisted the world’s leading hospitality firm in building data pipelines for pre-merger data integration planning

Machine LearningData AnalysisTime-Series ForecastingK-Means Clustering

Business Analyst

Nov 2017 – May 2019 · 1 yr 6 mos

Data Collection and Analytics: Successfully collected and merged data from diverse structured and unstructured sources to derive actionable insights. These insights played a crucial role in the effective management of client's Loyalty Program. Implemented advanced analytics techniques to uncover hidden patterns and trends in the data. This analytical approach enabled proactive decision-making and taking corrective action
KPI Development and Visualization: Developed Key Performance Indicators (KPIs) and visualized metrics in Tableau for various products, enabling the leadership team to derive actionable insights

Data AnalysisData VisualizationTableau