Aravind (Sasi Nair) Sasi Nair Purayath
AI – Data Specialist
Experience
AI – Data Specialist
Emirates Islamic Bank
- Architected and deployed LLM based AI agents, RAG pipelines, and vector search solutions for decision support across retail banking department.
- Developed and shipped robust AI pipelines with guardrails, error handling, monitoring, and fallback logic ensuring high reliability outcomes and compliance with data privacy.
- Developed and deployed ML models to identify transactional anomalies, improving fraud detection and risk assessment in high-volume datasets for credit risk modelling.
- Built, evaluated and fine-tuned ML models to generate propensity scores for customers used to drive personalized targeting campaigns for credit cards and personal finance/loan products.
- Developed an NLP pipeline using BERT embeddings and spaCy NER for SMS/email analysis and customer query logs.
- Trained machine learning models using Isolation Forest to classify user behaviour and detect anomalies.
- Extracted, cleaned, enriched and feature engineered datasets from different sources to build feature stores that powered ML model training.
- Led development of dashboards using Power BI, Grafana, and Prometheus to monitor model performances, KPI trends, and marketing metrics.
- Built multi-touch attribution models using logistic regression and time-decay weights to evaluate lead quality.
- Developed scalable ETL pipelines from CRM, T24, SAP, and ERP, supporting millions of monthly transactions.
- Integrated testing and CI/CD workflows for robust data pipeline deployment.
Senior Data Specialist (AI/ML)
Flipkart
- Built and deployed reinforcement learning ad personalization system (K-Means clustering, XGBoost, collaborative filtering) using Azure ML; monitored via A/B tests achieving measurable engagement uplift.
- Trained XGBoost model via Azure ML for geo-targeted campaigns; integrated with marketing platforms and monitored performance against campaign KPIs.
- Deployed BERT-based classifier via Azure Functions, orchestrated bi-weekly retraining on Databricks, integrated with Elasticsearch for product catalog updates.
- Extracted, cleaned, and visualized data from multiple sources to curate high-quality datasets for machine learning models, and evaluated, fine-tuned, and deployed those models using Azure or internal hosting solutions.
- Translated marketing/product team requirements into ML solutions; communicated complex model behavior in business terms to non-technical stakeholders.
- Analyzed 50M+ row datasets using PySpark and SQL for near real-time decision support; built scalable data pipelines supporting analytics and ML feature stores.
- Improved push notification CTR by 11% by analyzing heatmap data (views, clicks, hovers) and optimizing key landing pages.
Analyst
Muvin
- Mentored developers and employees on ML and automation technologies, creating high-value POCs and MVPs.
- Designed and deployed a custom ML model for feedback text analysis, integrated as a reusable AI component across projects.
- Developed, implemented, and optimized ETL data pipelines to efficiently process and integrate large-scale datasets from diverse sources into centralized platforms.
- Deployed Grafana and Prometheus for real-time monitoring of Azure infrastructure, enhancing system reliability and performance tracking.
Data Science Intern
Flip Robo
- Designed and implemented A/B experiments to optimize customer retention and loan offerings for a banking client.
- Implemented lifecycle automation using Azure ML pipelines for retraining a loan default classifier every two weeks, with triggers based on data drift monitored via MLflow.
- Worked on real-time fraud detection models on scalable ML infrastructure using containerized workflows via Kubernetes and CI/CD pipelines on AWS SageMaker.
- Developed continuous data drift monitoring using MLflow and SageMaker model monitor to ensure prediction reliability in production.
Data Analyst
Swiggy (Bundl Technologies)
- Used a Thompson sampling multi-armed bandit approach in production (Python + Flask API) to dynamically serve push notifications across user segments; achieved a 7% CTR uplift over static rules.
- Utilized association rule mining on transactional data to identify frequently co-ordered item combinations and informed bundling and cross-selling strategies.
- Scraped competitor pricing daily using Selenium and analyzed price elasticity using regression models in pandas/statsmodels; fed into the internal pricing recommendation dashboard in Power BI.
- Used uplift modeling and counterfactual inference techniques to isolate the true effect of personalized promotions and targeted campaigns.
- Worked on multiple machine learning POCs related to product pricing elasticity and customer segmentation.
- Built demand forecasting models to predict order volumes and optimize supply chain logistics.
Consultant - Freelance
Vrindavan Consultants
- Enabled the team to adopt data-driven scheduling and inventory planning, improving resource utilization by 15%.
- Conducted competitor analysis and provided data-backed recommendations for local SEO and marketing spend allocation.
- Created a pricing optimization model using Excel and Python to recommend tiered service bundles based on seasonal demand.
- Built a Power BI dashboard to track inquiries, service requests, and customer lifetime value across regions.
- Improved lead conversion by analyzing customer acquisition data and service patterns.
Associate Financial Reporter
Digital Nirvana
- Attained solid understanding of financial markets and exchanges; worked with finance teams to assist with quarterly and yearly financial press releases.
- Partnered with executives to analyze workflow data, identifying bottlenecks and reducing ETAs; ensured data quality and consistency by implementing monitoring processes and best practices.
- Supported data analysis for troubleshooting and report generation using Power BI and SQL for daily and quarterly earnings reports for multiple clients.
- Automated quarterly earnings report generation using SQL queries and Power BI dashboards for 10+ clients, significantly reducing manual effort and standardizing reporting templates.
Industries Experience
See where this freelancer has spent most of their professional time. Longer bars indicate deeper hands-on experience, while shorter ones reflect targeted or project-based work.
Experienced in Banking and Finance (3 years), Retail (2 years), Food and Beverage (1.5 years), Professional Services (1 year), and Information Technology (0.5 years).
Business Areas Experience
The graph below provides a cumulative view of the freelancer's experience across multiple business areas, calculated from completed and active engagements. It highlights the areas where the freelancer has most frequently contributed to planning, execution, and delivery of business outcomes.
Experienced in Business Intelligence (8.5 years), Marketing (4.5 years), Information Technology (3.5 years), Finance (2.5 years), Supply Chain Management (2.5 years), and Product Development (2 years).
Summary
AI & Data Specialist with 7+ years of experience designing and delivering innovative AI-driven solutions and data products across industries. Skilled in managing end-to-end AI/ML modeling, building automation pipelines, and deploying scalable, real-time AI systems. Expertise in Generative AI, LLMs, and Agentic AI, with a focus on collaborating with cross-functional teams to integrate advanced technologies while ensuring scalability, reliability, and compliance.
Skills
Ai/ml Algorithms
- Transformers
- Diffusion Models
- Gradient Boosting Machines (E.g., Xgboost, Lightgbm, Catboost)
- Random Forests
- Support Vector Machines (Svm)
- Convolutional Neural Networks (Cnns)
- Recurrent Neural Networks (Rnns) And Lstms
- Graph Neural Networks (Gnns)
- Deep Q-networks (Dqn)
- Clustering (E.g., K-means, Dbscan)
- Statsforecast
Business Tools
- Microsoft Dynamics Crm
- Erp
- Power Bi
- Azure Devops
Tools And Frameworks
- Pytorch
- Tensorflow / Keras
- Scikit-learn
- Hugging Face Transformers
- Pandas
- Numpy
- Dask
- Apache Spark (Pyspark)
- Sql
- Snowflake
- Bigquery
- Redshift
- Databricks
- Docker
- Kubernetes (Aks)
- Aws Sagemaker
- Google Vertex Ai
- Azure Ml
- Git
- Github
- Power Bi
- Streamlit
- Qliksense
- Copilot Studio
- Claude
Coding Languages
- Python
- Javascript
- Sql (Postgresql, Sql Server)
- C++
Azure
- Ai Foundry
- Cognitive Services
- Azure Function App
- Azure Speech Studio
- Azure Devops
- Azure Key Vault
- Azure Openai
- Azure Data Factory (Adf)
- Form Recognizer
- Logic Apps
- Rag
Agentic Ai Frameworks
- Mcp (Model Context Protocol)
- Langgraph
- Pydantic
- Haystack
- Semantic Kernel
- Autogen
- Crewai
- Aws Bedrock Agent Builder
- Evaluation & Guardrails
- Model Monitoring
Languages
Education
CMS College of Engineering and Technology
Bachelors in Engineering, Electronics and Communication · Electronics and Communication · Coimbatore, India
Profile
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