PROFESSIONAL SUMMARY:

• Certified Busines Intelligence and Data Professional with 7.5+ years of experience in Data Science, Margin Improvement, Operations Analytics, Evidence - Based Decision Making and Databases
• Partnered with Senior Management on enterprise-wide special projects and supported decisionmakers by designing effective business processes and providing data driven answers to achieve business goals
• Solid quantitative background in Technology and Management with exceptional ability to learn and adapt to newer technologies and deliver solutions
• Exposure of multiple domains, such as Telecom, Supply Chain, Finance, Management consulting, etc.
• Expertise in entire data science project life cycle, including Business Understanding, Data Understanding, Data Preparation, Machine Learning Algorithms, Model Evaluation and Data Visualization
• Extensive Knowledge in implementation of Recommendation System, Deep learning, Text Analytics
• Knowledge and experience with AWS services (S3, Glue, Redshift, Quicksight, Sagemaker, Lambda)
• Experienced PL/SQL programming (DDL, DML, and DCL) skills. e.g. creating Stored Procedures, User Defined Functions, Constraints, Window Functions, Joins, Indexes, Triggers, Tables, Views
• Proficiency in visualization tools and packages. i.e. Tableau, Power BI, Matplotlib, Seaborn and ggplot
• Strong knowledge of Linux/Unix Shell Commands

TECHNICAL KNOWLEDGE:

Statistical Programming & Cloud Analytics : Python, TensorFlow, keras, MongoDB, AWS, Apache Spark, R, PostgreSQL, Unix, Tableau

Algorithm Expertise: Machine Learning: Linear Regression, Logistic Regression, Decision Tree, SVM, Time Series Analysis, Ensemble Algorithms (Random Forest, Voting- Hard and Soft, Bagging, Boosting, Xgboost) Natural Language Processing: Sentiment Analysis, NLTK, TF-IDF, N-Grams Neural Network & Computer Vision: Convolution Neural Network, Object Detection, LSTM AWS: S3, Redshift, Athena, Glue, Rekognition, Quicksight, CloudFront, Lambda, SageMaker

Statistical Analysis: Monte Carlo Simulation, Hypothesis Testing, Industrial Statistics, Experimental Design, ANOVA

Database Expertise: Database Design: Star and Snowflake Schema, Fact and Dimension table creation Database Administration: (Materialized) View creation, Access ControlNQuery Performance Tuning: Common Table Expressions, Procedures, Partitioning, Window Functions

Data Engineering : PySpark, Hadoop Fundamentals, MongoDB, Apache Airflow s

PROFESSIONAL EXPERIENCE:

Confidential, Boston, MA

Data Science Analyst

Responsibilities:

• Partnered with Senior Director Data Science to visualize advertisement campaign performance and generate insights for profitable Facebook custom audience generation and content engagement
• Understood Viacom marketing process and custom audience data points and performed text analytics , feature engineering, Natural language Processing (NPL) and ensembled algorithms to find higher gross margin influencers, customer data source, brand partner and custom audience attributes
• Researched the most profitable lookalike percentage for Facebook custom audience generation; Used Python packages to perform statistical analysis and Seaborn to present customized boxplots to present the insights
• Created document term matrix , dummy variables of text and categorical variables using one hot encoding and target variable of Gross margin, based on business rules of cost and revenues per 1000 impressions
• Selected top 30 features with maximum Pearson’s correlation and employed correlation matrix to remove features with collinearity
• Modeled a Hyper parameter tuned Random Forest on ad campaigns with greater than 75% margin, to get the insights about most profitable Influencers, Marketing Partners, Brand Campaigns, Customer Data source and criteria for custom audience creation
• Created the analysis dashboard in Tableau on the account profitability and level of engagement
• Implemented Data collection and transformation in AWS cloud computing platform using S3, Athena, Glue, Redshift, PostgreSQL, Quicksight
• Performed Data analysis, visualization, and machine learning in Jupyter notebook using Python packages

Confidential, Boston , MA

Graduate Teaching Assistant

Responsibilities:

• Reinforced faculty with additional course material in execution of lesson plans; conducted office hours and co-taught statistical concepts and predictive algorithms to 50 graduate-level students per quarter
• Designed a hackathon problem for students to implement Naive Bayes algorithm with gradient descent without using the Scikit-learn package and writing user defined functions to implement the algorithm

Confidential, Boston , MA

Business Analyst

Responsibilities:

• Discovered and visualized current state of business using Human-Centered Design approaches for wider stakeholder ; defined problem statements, translated functional requirements to system requirements by creating user stories, wireframes and workflows
• Reduced delayed student payroll distribution anomalies by 50% for 3500+ student employees ; Interviewed all stakeholders (college administrators, Finance, HR, Student employment), propagated best practices to wider departments and developed a workflow-based process to manage intra-department requests
• Designed a decision-making tool for senior leadership to enhance planning and implementation of business functions and evaluate preparedness for launch of new campus in Canada
• Performed sentiment analysis (Python) of alumni and student community feedback on Data Analytics program of College of Professional Studies

Confidential

AWS Data Engineer /Sr. Data Analyst

Responsibilities:

• Established Amazon S3 bucket to create a data lake consisting historical and current records from 2009 onwards for a central reporting solution
• Configured AWS Glue Crawlers to scan data sets and populate Glue Data Catalog, which served as a central metadata repository
• Utilized Python, Amazon Athena, Amazon Redshift, and Amazon EMR to perform data exploration and data analysis on data cataloged in Glue
• Designed and developed Insights reports on AWS Quicksight for client deliverable
• Exposure to Hadoop ecosystem and used Apache Hive to access HDFS data for further data analysis

Confidential

Assistant Manager Data Analytics/Operations Excellence

Responsibilities:

• Predicted quarterly topline revenue using Autoregressive Model to provide a leading indicator for revenue projection for senior management
• 38% uplift of purchase volume and improvement in site engagement of EMEA ecommerce client; engineered a Recommendation Engine ( Python ) to target users with most relevant products
• Partnered with Leadership in Key Performance Measures Development and spearheaded weekly Sales and Delivery Pipeline Review for BFSI Business Unit (BU) with annual topline of $130 Mn+
• Saved Revenue Loss of $40K per quarter due to staffing bottlenecks; developed lateral hiring process with Systems Approach to information flows, process lead times and approval authority structure of HRM, Sales and Project Delivery Units
• Instituted Profitability Improvement Program with tracking and monitor mechanism for unit of 1100+ employees; examined cost and profit components of accounts and liaised with 5 Delivery Partners and 20+ Account Managers
• Designed a Gross Margin Tool for account managers and Delivery partners to enable them to simulate what if scenarios of staffing, billing rate, utilization to takes margin sensitive decisions
• Reduced information lead time from 2 business days to 4 hours for weekly COO review reports and saved 28 hours of efforts per week for organization; designed and implemented Data Integration Pipeline in Business Intelligence Development Studio (BIDS) for Central Operations Analytics Group
• Augmented BU performance metrics from bottom 2 to top 2 performing Units; investigated enterprise-wide data and reported actionable insights on Trend and Root Cause Analysis of operational metric deviations, Project Costing, People Pyramid, Employee Billability and Utilization, Salesforce, Microsoft Ax
• Empowered decision makers with data driven actionable insights; Utilized Python, R, SQL, Excel, and Tableau to extract, transform and perform analysis on the data from various sources

Confidential

Business Consultant

Responsibilities:

• Performed diagnostic study to improve procurement process, service levels and profitability of Navi Mumbai Municipal Transport
• Studied cost drivers and build a deterministic model to replicate current revenue and cost factors, used to quantify benefits from margin improvement initiatives
• Evaluated ERP system functionality compatibility with business goal and recommended modifications/enhancements to system functionality/business logic

Confidential

Software Engineer

Responsibilities:

• Championed end-to-end Billing & Customer care product solutions; programmed and deployed optimized PL/SQL scripts
• Provided L1/L2 Production & Incident Management Support in Unix environment for critical implementations within stringent Service Level Agreement of telecom sector
• Interpreted business requirements and converted it into SQL stored procedures for database specific projects, performed System Analysis, and Unit, Integration and User Acceptance Tests
• Developed Self-Service tools that enabled development teams to troubleshoot and maintain performance
• Assisted development teams with complex query tuning and schema refinements
• Improved quarterly SLA compliance report using Python packages for data analysis and visualization