• Responsible for development of cost analysis and fleet-route optimization models.• Achieved 30%+ cost savings versus the current-state planning number by analyzing the fleet structure for efficiency and also, major cost drivers to cut unnecessary items from overhead and headcount planning.• Analyzed current state processes, identified opportunities for efficiency gains, and implemented 20 process improvements using the lean six-sigma DMAIC methodology.

• Performed scraping on semi-structured text data and converted it into structured data using R.• Wrangled and analyzed the data and extracted new features to attain meaningful visualizations.• Performed time series analysis on that data and visualized the data using ggplot2.• Created a sentiment analysis model on the text to analyze the mood of the population on certain days of the week in the light of any political and militaristic changes across the state.• Consequentially, curbed politically ignited violence by 38% in the city by recommending appropriate number of work-head allocations for different locations based on their respective vulnerabilities.

• Worked with Machine learning algorithms like Linear Regressions, SVMs, Decision trees for classification of groups and analyzing most significant variables such as FTE, Waiting times of purchase orders and Capacities available and applied process improvement techniques.• Participated in feature-engineering such as feature creation, feature scaling, One-Hot encoding with Scikit-learn.• Converted raw data to processed data by merging, finding outliers, errors, trends, and missing values in the data.• Worked on Clustering and factor analyses for classification of data using machine learning algorithms.• Developed Descriptive statistics and inferential statistics for Logistics optimization, Average hours per job, Value throughput data to at 95% confidence interval.• Experience with risk analysis, root cause analysis, cluster analysis, correlation and optimization and K-means algorithm for clustering data into groups.• Coordinated with data scientists and senior technical staff to identify client's needs and document assumptions.

• Created database objects such as stored procedures, functions, tables, views, dynamic SQL in SQL server to fulfill modeling. Also handled slowly changing dimensions with type 2 and type 4 in T-SQL stored procedures.• Accomplished ETL process for initial and incremental load by developing SSIS packages by performing data cleansing, data transformation, and error handling.• Built various reports in SSRS by creating tables, matrices, lists, charts, drill down, drill through reports and setting cascading parameters and conditional formatting.• Involved in development and application of software to respond to customer requirements and to cost-effectively provide a means of analyzing, producing, distributing, and storing information.• Contributed $32,000 savings for project and brought down revenue prediction error from 15% to 5%.

• Knowledge transfer and assessment on Python/R, SQL, SDLC & Agile methodology• Brainbench certifications: Microsoft Dot Net Framework, SQL, Agile Methodology• Pluralsight certifications: Data Interpretation with Statistical Models, Python, Microsoft Team Foundation Server (TFS)