Krishna Bastola Email & Phone Number

Baltimore, Maryland, Usa

As a Data Analyst, I specialize in analyzing large datasets to uncover trends and provide actionable insights to business stakeholders. I have developed predictive models to forecast customer behavior and enhance marketing strategies, utilized SQL for ETL processes, and created interactive dashboards with Tableau. Additionally, I have automated data workflows using Python to boost efficiency and collaborated with cross-functional teams to define and monitor business KPIs. My expertise includes implementing machine learning algorithms for credit risk assessment, conducting A/B testing to improve marketing campaigns, designing and maintaining data pipelines for real-time analysis, performing data quality assessments, and developing customer segmentation models to drive engagement. I also lead training sessions on data analysis tools and best practices, optimize SQL queries for performance, and provide ad-hoc data analysis to support strategic decision-making.Key Contributions:- Conducted A/B testing, leading to a 15% increase in conversion rates.- Developed customer segmentation models, increasing engagement by 10%.- Implemented data governance practices, reducing data discrepancies by 20%.- Optimized SQL queries, reducing query execution time by 30%.- Automated data workflows for enhanced efficiency and accuracy.- Defined and tracked business KPIs in collaboration with cross-functional teams.- Led training sessions to improve team efficiency in data analysis.

Columbus, Ohio, Usa

As a Data Analyst at Northern Trust, I specialize in data analysis to support investment strategies and portfolio management. I extract and transform data using SQL and Python, and develop reports and dashboards with Power BI. My role involves statistical analysis to identify performance drivers, collaboration with IT and business teams for data governance, and developing automated reporting tools. I present findings to senior management, design data models for predictive analytics, and optimize data retrieval processes, reducing query times by 40%. Additionally, I conduct market research, create custom visualizations, maintain a central data repository, train junior analysts, implement machine learning algorithms, and provide data-driven recommendations, resulting in a 10% increase in portfolio returns.Key Contributions:- Conducted detailed data analysis to support investment strategies and portfolio management.- Extracted, cleaned, and transformed data using SQL and Python.- Developed and maintained reports and dashboards using Power BI.- Performed statistical analysis to identify performance drivers and risk factors.- Optimized data retrieval processes, reducing query times by 40%.- Developed custom visualizations in Power BI to provide deeper insights into key performance indicators.- Provided data-driven recommendations that resulted in a 10% increase in portfolio returns.

Annapolis, Md, Usa

As a Data Analyst at Ford Motor, I analyzed manufacturing data to enhance production efficiency and reduce costs. I utilized R and Python for statistical modeling and data visualization, developed data collection systems to optimize statistical efficiency and data quality, and collaborated with engineering teams to understand data requirements and deliver insights. I conducted root cause analysis on production issues, provided data-driven recommendations, and created detailed documentation of data analysis processes. Leveraging machine learning techniques, I predicted maintenance needs and enhanced production planning. I implemented real-time monitoring systems, designed Tableau dashboards for key production indicators, and automated routine data analysis tasks using Python. Additionally, I conducted time-series analysis to forecast production demands, improved data accuracy through validation protocols, analyzed supply chain data, provided staff training, and identified process improvements that led to a 15% reduction in waste and rework.Key Contributions:- Conducted root cause analysis on production issues and provided data-driven recommendations.- Leveraged machine learning techniques to predict maintenance needs and enhance production planning.- Implemented real-time monitoring systems to track production metrics and identify inefficiencies.- Designed and deployed dashboards in Tableau to provide instant visibility into key production indicators.- Automated routine data analysis tasks using Python scripts, reducing analysis time by 50%.- Improved data accuracy by developing and enforcing data validation and cleaning protocols.- Identified and implemented process improvements that led to a 15% reduction in waste and rework.