Exploratory projects on modern and open data engineering and AI/ML solutions
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Assessing your cultural and operational fit
attrition-analytics-xai-ensemble
September 23, 2025 – October 11, 2025
ML project on attrition prediction with PCA analysis, engineered features, XGBoost/CatBoost ensembles, SHAP explainability, and GNNs for relational modeling — served via Flask APIs.
View Projectdatalake_openformat
September 14, 2025 – September 16, 2025
Exploring Apache Hudi, Apache Iceberg and Delta Lake capabilities for Architectural trade-off and decision making
View ProjectHR_Attrition_Analysis
September 5, 2025 – September 5, 2025
HR Attrition analysis with fairness-aware ML — from multi-source integration, feature engineering, bias mitigation, and API deployment
View ProjectHR_ModernDataPipeline
September 2, 2025 – September 14, 2025
Airflow-orchestrated pipeline simulating CDC from Postgres via Debezium → Kafka. Spark Streaming loads events into Delta Bronze and transforms to Silver, while DBT powers the Gold layer for analytics.
View ProjectPreditiction_LSTM_DeepLearning
August 26, 2025 – August 26, 2025
LSTM-based deep learning model to predict next day stock prices, combining technical indicators, Bayesian tuning and hyperparameter optimization with advanced time-series modeling
View ProjectDataBricks_DLT_Pipeline
August 25, 2025 – September 2, 2025
Implements a data pipeline using DLT in Databricks (Delta Lake) and uses medallion layering in Delta Lake
View Projectstreaming-delta-scd
August 16, 2025 – August 26, 2025
Kafka + Spark Streaming project demonstrating real-time ingestion, Delta Lake with windowed aggregations, watermarking, schema evolution, and SCD Type 2 handling, with readers in Spark and DuckDB.
View Projectprice-prediction-dask
July 9, 2025 – July 11, 2025
A lightweight Dask-powered tool for parallel price prediction using Linear Regression & Random Forest, with a simple Gradio UI
View ProjectAgenticAI_LLM_Analyzer
July 7, 2025 – August 25, 2025
A multi-agent stock analysis tool using CrewAI, LLM/OpenAI and vector embeddings to combine technical indicators, news sentiment, and social media signals into orchestrated insights.
View ProjectCultural Fit Analysis
The candidate exhibits a strong inclination towards self-driven learning and project-based skill development, which aligns well with a culture that values continuous improvement and practical application. The breadth of personal projects, especially those exploring architectural trade-offs (e.g., datalake_openformat), indicates a curious and analytical mindset. The focus on end-to-end solutions, from data ingestion to model deployment and explainability, suggests a holistic approach to problem-solving. However, the lack of team-based or professional experience makes it difficult to fully assess collaboration and adaptability in a corporate setting.
Soft Skills & Operational Fit
The candidate's project descriptions indicate a proactive and hands-on approach to learning and applying new technologies. The diversity of projects suggests an ability to tackle complex problems and explore different architectural patterns. However, without specific psychometric or English test scores, it's difficult to assess communication clarity, logical reasoning, work attitude, stress handling, or team collaboration directly. The detailed project descriptions suggest good technical communication.