SUMMARY:

• Over 8 years of diverse experience in data & business analysis, project management and technology consulting with a passion for solving Business problem through advanced analytics and innovative data solutions
• Strong experience in data science, machine learning and artificial intelligence using different methodologies like Regression, Bayesian, Decision Trees, Random Forests, SVM, Kernel SVM, Naïve Bayes, K - means Clustering, Natural Language processing (NLP) among others
• Scientific thinking and ability to invent, a track record of thought leadership and contributions
• Strong knowledge in applying big data/advanced analytics to identify and exploit data with positive business impact
• Proven track record of diving into the data to discover hidden patterns using predictive analysis
• Self-starter and able to work interactively and independently with stakeholders. Expertise in managing multiple projects and teams with an excellent track record.
• Experience with SQL queries to perform data analysis, data mapping and data validation of the transformed data output
• Proficiency in statistical programming languages Python (numpy, pandas & scikit-learn)
• Experience in all phases of ETL for data preparation and loading
• Data visualization experience in Tableau, Python (numpy, pandas & scikit-learn) and R (ggplot)
• Familiarity with common API’s like SOAP and REST.
• Knowledge of distributed computing platform like Hadoop, Spark & Hive
• Top 1% in Kaggle among 2 million + active Data science members worldwide

TECHNICAL SKILLS:

Management skill: Data governance, Strategic planning, Project Management, Agile

Machine learning: Statistics & Probability, Linear Regression, Logistic regression, Decision Tree, Random Forest, SVM, K-means Clustering

Languages: Python (numpy, pandas, scikit-learn), SQL, R

Visualization: Tableau, matplotlib, seaborn, Power BI

Cloud computing: AWS (EC2, S3, DynaboDB, Redshift, Aurora, VPC, SQS), Microsoft Azure

Databases: Oracle, MS Access, MS SQL Server

PROFESSIONAL EXPERIENCE:

Confidential, Pittsburgh, PA

Data Scientist

• Using Python and Tableau to identify customer trends affecting 15% increase in revenue for ‘Commercial’ and ‘Government Programs’ for Client ( Confidential )
• Collecting and analyzing data to solve business problems and clearly communicating the benefits, risks and trade-offs to business by using Logistic regression, Decision trees and Random forest models
• Established and managing data governance process to define data quality and standards resulting in 10% reduction in operational costs
• Collaborated with business to understand company needs and devise possible solutions using data
• Analyzed and solved business problems, and found patterns and insights within structured and unstructured data
• Cleaned, analyzed and did featuring engineering as part of data pre-processing
• Implemented new statistical and mathematical methodologies to identify hidden patterns
• Used algorithms and programming to efficiently go through large datasets and apply treatments, filters, and conditions as needed
• Created meaningful data visualizations to communicate findings and relate them back to how they create business impact using Tableau
• Presented proposals and results in a clear manner backed by data and coupled with actionable conclusions to drive business decisions

Confidential, Windsor, CT

Data Scientist

• Led cross-functional team to develop ‘Supplier Portal’ website for 50k+ third party vendors resulting in 10% cost savings ($300k) per year by eliminating manual efforts, reducing billing issues & cancelled orders.
• Used advanced analytics techniques like Clustering and Linear Regression to gain valuable insights that enabled clients to track Business performance and optimize pricing for vendors
• Completed Exploratory data analysis (EDA) in Jupyter and communicated results to Business
• Built models for highly imbalanced data sets using Bias/variance trade-off
• Developed and interpreted information by creating dashboards using Tableau that assisted management with decision making to enhance customer service
• Reviewed and analyzed customer behavior and trends to assist in solving business problems
• Responsible for generating ideas for product changes that improve key metrics
• Write SQL queries to perform data analysis, data modeling and prepare data mapping documents to explain the transformation rules from source to target tables
• Provided data analytics of the web-portal to the team for feedback and improvement
• Work with a variety of business units throughout the organization to help translate their requirements into specific analytical deliverables.

Confidential, Farmington, CT

Sr. Data Analyst

• Led data mapping, data modeling & ETL process for $18.4 Billion acquisition of ‘Goodrich’ for client ‘ Confidential ’
• Analyzed and reduced production incident count by 10% for HR/Payroll application by diagnosing recurring issues
• Scheduled and facilitated requirements gathering with HR, Payroll, finance and accounting teams to implement ADP eTime and ADP Enterprise v5 and ADP General Ledger and drove requirements for data collection and data modeling with data engineers.
• Created data modeling and data mapping document containing source, formulate transformational rules to populate target fields
• Performed data analysis to create reporting requirements by specifying inclusion & exclusion criteria, conditions, business rules and data elements to be included into the report
• Performed ad-hoc SQL query for data analysis
• Support PMO governance activities; defining and maintaining Project Management standards.

Confidential, San Jose, CA

Business Analyst /Data Analyst

• Worked as a Business and Data analyst for a critical ‘Partner Online Enablement’ portal to personalize, re-design and re-architect existing portal with an estimated 15% increase in revenue
• Led and executed complex data related analytical projects to drive
• Established a Business Analysis methodology around the agile as well as waterfall methodology
• Facilitated and managed Joint Application development (JAD) sessions with a committee of SMEs from various business areas.
• During various phases of testing documented problems reported by users and resolved them by analyzing issues against business rules.
• Routinely used complex SQL statements for data analysis, business analysis, testing and resolving business issues.