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Anik Biswas

@anikbiswas

Data Analyst with an M.Tech in Computer Science and hands-on experience turning transactional and customer data into reliable KPIs.

India

Message

What I'm looking for

I'm looking for a data analytics or business intelligence role where I can build reliable SQL, Python, and Power BI workflows, improve data quality, and deliver actionable KPI reporting.

I've delivered end-to-end analytics workflows for revenue, customer, and operational reporting, combining SQL data modeling, Python automation, DAX measures, and interactive Power BI dashboards. I reduced a representative SQL report runtime by approximately 93%, from 55 seconds to under 4 seconds, through query refactoring, join optimization, and composite indexing.

I've built data-quality workflows with Python and Apache Airflow, churn models using engineered behavioral features, and BI reporting models covering 18 KPIs. My work includes validation rules, audit reporting, cohort analysis, predictive modeling, and translating transactional and customer data into actionable reporting.

Experience

Work history, roles, and key accomplishments

Current

Independent Data Analyst

Current

Self-Directed

Jul 2024 - Present (2 years 2 months)

Reduced report latency by ~93% through query refactoring and indexing. Built automated data-quality workflows and delivered end-to-end analytics workflows for revenue, customer, and operational reporting.

SQL Python Airflow Power BI DAX Data Modeling Data Validation ETL

Data Analyst Intern

Afame Technologies

May 2024 - Jun 2024 (1 month)

Built a churn classification pipeline in Python and SQL, engineering 16 behavioral features and benchmarking models. Improved SQL reporting workflows by restructuring legacy queries and optimizing joins.

Python SQL scikit learn Feature Engineering Model Evaluation Query Optimization

Data Science Intern

Cognifyz Technologies

Mar 2024 - Apr 2024 (1 month)

Accelerated preprocessing runtimes by replacing loop-based transformations with vectorized Pandas operations. Improved recommendation-model evaluation by engineering interaction features and tuning XGBoost hyperparameters.

Python Pandas XGBoost Feature Engineering Cross Validation