Apr 2025 – Present · 1 yr 1 mo · Boston, Massachusetts, United States · On-site

• At the Massachusetts General Hospital (MGH) Voice Center, I build and apply AI/ML and digital signal processing (DSP) systems to advance the prevention, diagnosis, and treatment of vocal hyperfunction. My work focuses on architecting AI-driven systems for laboratory and ambulatory voice monitoring data, with a particular emphasis on the Lombard effect in both patients and healthy individuals—translating research into a clinician-ready voice science product for healthcar
• 𝑺𝒌𝒊𝒍𝒍𝒔
• Machine Learning · AI Explanability · Statistics · Deep Learning · Digital Signal Processing · voice Science

Jan 2025 – Present · 1 yr 4 mos · Boston, Massachusetts, United States · On-site

• Guiding students in applied AI & data science projects within the College of Engineering, drawing on industry experience to bridge the gap between classroom concepts and real-world product development.
• Building AI-driven academic platforms, including recommendation systems for student course selection and grading/assessment tools that simulate enterprise-scale product development lifecycles.
• Advising curriculum design to ensure students gain hands-on exposure to end-to-end AI product development, preparing them as industry-ready professionals.
• 𝑺𝒌𝒊𝒍𝒍𝒔 :
• Agentic AI Architecture · Large Language Models (LLM) · Retrieval-Augmented Generation (RAG) · Recommender Systems · Leadership · Mentoring

Jan 2023 – Mar 2024 · 1 yr 2 mos

• Served as Chief AI Scientist, working closely with the Founders to secure multi-million-dollar funding, by architecting GenAI and analytics platforms for enterprise clients and leveraging real-time Agentic AI orchestration to deliver explainable business insights.
• Designed and deployed a risk-based IRR predictive model for a $2B affordable housing finance organization — improving investment risk forecasting, profitability, and decision efficiency — and scaled it into a global FinTech product, creating a defensible MOAT.
• Spearheaded a delinquency prediction engine, strengthening credit-risk management through better risk identification, reduced defaults, optimized resource allocation, and cost savings.
• Provided strategic AI recommendations that influenced product innovation, customer experience, and market positioning.
• 𝑨𝒃𝒐𝒖𝒕 𝒅𝒗𝒊𝒆𝒘.𝒊𝒐
• Harnesses cutting-edge GenAI and Knowledge Graph technology to deliver actionable insights for data-driven decision-making. The platform unifies disparate data into a centralized, compliant, and scalable system — accelerating analytics, business intelligence, and growth for enterprises.
• 𝑺𝒌𝒊𝒍𝒍𝒔
• Functional Capabilities: Agentic AI orchestration, retrieval-augmented generation (RAG), knowledge graphs, credit risk modeling, delinquency prediction, investment forecasting.
• AI Models & Tools: LangGraph, LangChain, Neo4j, XGBoost, IRR modeling frameworks.
• Cloud & Automation: AWS, CI/CD pipelines, MLOps for financial AI systems.
• Leadership & Strategy: Chief AI Scientist leadership, startup advisory, fundraising enablement, AI platform architecture, product innovation strategy.

Apr 2022 – Apr 2024 · 2 yrs

• Led Condé Nast’s Data Science & Analytics function, setting the data strategy and driving AI-powered Content Intelligence, customer segmentation, and AdTech transformation across global brands (Vogue, The New Yorker, Wired, Architectural Digest).
• Partnered with Marketing and Commercial Science to embed AI into business workflows, delivering first-party, cookie-less AdTech solutions and a global-scale recommendation engine for Vogue, GQ, Wired, The New Yorker, and Pitchfork.
• Advanced context-aware search, universal entity extraction, personalization systems, and dynamic pricing models, boosting subscription and advertising revenue while shaping the company’s next-generation data products.
• 𝑺𝒌𝒊𝒍𝒍𝒔
• Functional Capabilities: Context-aware search, sequential modeling, multimodal search, personalized user engagement, AI-powered content intelligence, AdTech segmentation, first-party cookie-less solutions, universal entity extraction, customer segmentation.
• AI Models & Algorithms: RoBERTa, LSTM, CLIP (multimodal), ANNOY, Llama ( LLM- Gen AI), LangChain, XGBoost.
• Cloud & Automation: AWS SageMaker, AWS Lambda, AutoML, LLMOps.
• Applications: Text-to-image search, image tagging, persona modeling, chatbot development, content classification.
• Leadership & Management: Stakeholder management, strategic planning, AI-driven decision making, cross-functional team collaboration.

Feb 2022 – Apr 2022 · 2 mos

• Leveraged advanced analytics and machine learning to uncover deep insights and drive strategic decisions in Business Banking at Commonwealth Bank. Spearheaded data-driven projects to enhance customer experiences and operational efficiencies
• 𝑺𝒌𝒊𝒍𝒍𝒔 :
• Functional Capabilities:Revenue Forecasting, Risk Management, Customer Lifetime Value Prediction, Operational Efficiency Enhancement, Data-Driven Strategy Development, Risk Factor Assessment.
• Technical Components:Classical Machine Learning (Regression), AutoML (PyCaret), Data Modeling, Risk Management, Exploratory Data Analysis (EDA), Factor Analysis in Financial Services

Feb 2021 – Feb 2023 · 2 yrs · Hybrid

• Mentored and inspired students in data analytics, AI/ML, and applied mathematics, bridging academic learning with industry applications.
• Led workshops, guided capstone projects, and fostered practical skills development through hands-on training and mentorship.
• Collaborated with academia, AI researchers, and industry professionals to enhance curriculum design, prepare students for real-world success, and shape the next generation of data scientists.

Feb 2021 – Feb 2022 · 1 yr

• Spearheaded the establishment of a Center of Excellence (AI Digital Lab) for AI Innovation & Design in collaboration with leadership, building high-performing AI teams and delivering enterprise-scale healthcare AI solutions for global pharma clients including Moderna, Pfizer, and Novartis.
• Designed a SaaS AI product — Smart OCR Engine (CNN-based) using PyTorch to convert clinical documents into machine-readable text as part of Robotic Process Automation (RPA), streamlining healthcare data workflows.
• Developed an AI-powered real-time audio monitoring system for patient care, leveraging edge-optimized models (TFLite, ONNX) and advanced DSP (source separation, beamforming), integrated into a CI/CD MLOps pipeline with automated ingestion, monitoring, and retraining in hybrid cloud environments.
• Built an Explainable AI (XAI) product to interpret deep sequential models (CRF-LSTM) for Named Entity Recognition, applying LIME, SHAP, and Integrated Gradients to enhance transparency, trust, and Responsible AI adoption in clinical workflows.
• 𝑺𝒌𝒊𝒍𝒍𝒔
• Functional Capabilities: SaaS product design, AI-powered data transformation, healthcare data accessibility, Robotic Process Automation (RPA), Explainable AI (XAI), model transparency and interpretability, model accuracy monitoring, drift detection (PSI, KS Test, KL Divergence), Responsible AI, HIPAA/GDPR compliance, Federated Leraning
• AI Models & Algorithms: Deep Sequential Models (CRF-LSTM), Named Entity Recognition (NER), Smart OCR Engine (CNN-based), XAI tools (LIME, SHAP, Integrated Gradients).
• Leadership & Management: Stakeholder collaboration, AI product development, operational strategy, Center of Excellence (CoE) establishment.

Sep 2019 – Feb 2021 · 1 yr 5 mos

• Media benchmarks & ROI insights: Conducted media portfolio & regression analysis across channels to measure productivity, effectiveness, profit margins, and short/long-term ROI, driving actionable investment decisions.
• Delivered product assortment intelligence using Bayesian techniques & BERT, powering a Recommendation Engine that optimized SKUs and improved marketing efficiency.
• Digital Marketing Mix Modeling (MMM): Designed MMM for E-commerce and Brand Homes across Ireland, Scotland, and the US using linear programming, optimizing digital spend (Search/Social) and achieving an estimated 3–5% sales uplift at equal or lower budgets.
• Supply chain & attribution: Improved supply chain efficiency with demand forecasting (ARIMA) & Market Basket Analysis (Apriori). Developed multi-touch attribution models (Hidden Markov Models) to compare planned vs. actual costs in programmatic & direct-to-consumer marketing.
• 𝑺𝒌𝒊𝒍𝒍𝒔 :
• AI Models & Algorithms: Hierarchical Bayesian Models, BERT, ARIMA, Apriori, Hidden Markov Models, Viterbi Algorithm, regression, linear programming.
• Cloud & Automation: Azure Cloud Platform, demand forecasting pipelines, media attribution models.
• Marketing Analytics Tools: Salesforce Einstein, Datorama, Digital Catalyst (BCG), Gain Theory Sensor, Global Performance Suite, Google Analytics, DCM, Shopalyst, Facebook Business Manager.

Apr 2017 – Sep 2019 · 2 yrs 5 mos

• Built scalable data pipelines to migrate B2C customers’ PII data from EDW and applied inferential statistics on purchase/sales history to drive customer segmentation and personalized promo-code assignments.
• Developed predictive revenue models using Google Shopping ad clicks, incorporating cross-sell and up-sell signals to improve campaign ROI across multiple product categories.
• Delivered consumer intelligence by mining social media data for FMCG brands, enabling data-driven engagement strategies and new product innovation.
• Implemented CLV and propensity models to strengthen customer segmentation, improve loyalty, and reduce churn.
• Enhanced brand performance with real-time social media analysis , supporting agile marketing adjustments that increased engagement and sales.
• 𝑺𝒌𝒊𝒍𝒍𝒔 :
• Functional Capabilities: Customer segmentation, predictive modeling, retention strategy, marketing analytics, personalization, CLV modeling, social media intelligence.
• Tech & Tools: Data pipelines, EDW, SQL, Google Shopping Ads integration,Regression, tree-based models,propensity models, Social media analysis
• Business Impact: Revenue forecasting, brand engagement, campaign optimization, FMCG/CPG analytics.

Apr 2015 – Mar 2017 · 1 yr 11 mos

• Developed and improved Apple’s Online Sales and Service data management, optimizing queries and performance using SQL, Teradata Procedures, Python, and customized APIs, and built a sophisticated data curation mechanism for the Enterprise Data Warehouse (EDW), resulting in enhanced reporting capabilities.
• Engineered Apple Payment Gateway (APG) A/B Testing data for the Global Business Intelligence core.
• Built User Data Management (UDM) and Data Quality Management (DQM) systems at Apple,
• implementing process automation using Informatica and Python to ensure data integrity and usability across various systems.
• 𝑺𝒌𝒊𝒍𝒍𝒔 :
• Big Data, Enterprise Data Warehouse, SQL, Teradata, Informatica, Power BI, Python, Excel.

Aug 2013 – Mar 2015 · 1 yr 7 mos

• Developed and implemented advanced Data Analytics and IoT-Based Condition Monitoring Solutions to modernize aging electrical infrastructure, leveraging Isolation Forests and Tree-based models for anomaly detection.
• Integrated real-time data from IoT devices (vibration, temperature metrics) using SQL for data storage and querying, and implemented time-series analysis and clustering techniques for monitoring equipment health, facilitating the shift from time-based to condition-based maintenance.
• Enhanced operational efficiency and automation for B2B and B2C businesses across various industrial sectors by utilizing the Enterprise Data Warehouse (EDW) for data storage, and Python and UNIX Shell Scripting for process automation and analysis.
• 𝑺𝒌𝒊𝒍𝒍𝒔 :
• Classical Machine Learning - Isolation Forests, Tree-based Models,
• IoT Devices, SQL, Time-Series Analysis, Clustering Techniques, Enterprise Data Warehouse (EDW), Python, UNIX Shell Scripting.