SUMMARY:

• With Over 10 years of experience working as a Data Scientist and a master’s degree in Statistics, I have a vast knowledge working with a wide range of datasets, identifying trends and interpreting results into actionable steps.In my previous jobs, I have worked on the following projects:
• Built regression model to identify best customer profile Built product recommender system to offer products based on user purchase history Performed market basket analysis, identifying upsell and cross sell opportunities Built cluster model using social media followers and identified 4 different target groups to optimize marketing spending Created monthly dashboards on product usage, website visits, customer inquiries, new contracts and cancellations Created a monthly retention report and maintained Sales and Run - rate database

WORK EXPERIENCE:

Data Scientist

Confidential - Dallas, TX

• Built K - means cluster model to group >200K customers into 4 categories, identifying best customer profiles
• Using Apriori algorithm, performed market basket analysis on >300 products identifying upsell and cross sell opportunities with >5% lift
• Applied logistic regression model, to build product recommender system with 82% accuracy, aimed at increasing sales by 20%
• Optimized email journeys by improving sent day of week and time of day, with the goal of improving open rate and clickthrough rate by 50%
• Worked with stakeholders to identify opportunities for leveraging company data to drive digital marketing business solutions
• Mined and analyzed data from multiple data sources using appropriate techniques to drive optimization and improvement of digital marketing business strategies
• Developed artificial intelligence stories using Salesforce AI toolset
• Coordinated with different functional teams to develop custom models and algorithms
• Developed processes to monitor and analyze model performance and data accuracy

Data Scientist

Confidential - Los Angeles, CA

• Built cluster models, created customer profile segmentation, identified new target groups
• Built Churn model to predict customer life expectancy
• Created inventory and order management databases in SQL, improved product tracking Created meaningful data visualizations to track and predict long term sales trends
• Applied machine learning techniques and developed predictive and statistical models by applying best
• In class modeling techniques
• Wrangle data and analyzed trends by making visualizations using mat plot lib in python
• Created a visual dashboard to track sales by department, best & worst performing products
• Presented proposals and results in a clear manner backed by data and coupled with actionable conclusions to drive business decisions

Senior Data Quality Associate

Confidential - New York, NY

• Performing data profiling and analysis on different source systems that are required for Customer Master
• Identifying the Customer and account attributes required for MDM implementation from disparate sources and preparing detailed documentation
• Presented DQ analysis reports and score cards on all the validated data elements, to the business teams and stakeholders
• Used Data Quality validation techniques (Accuracy, Validity, Conformity, Completeness, Timeliness, Coverage) to validate Critical Data elements (CDE) and identified various anomalies
• Interacted with the Business teams and Project Managers to clearly articulate the anomalies, issues and findings during data validation
• Extracted data from different databases as per the business requirements using SQL
• Generated Daily, weekly, monthly reports for various business users according to the business requirements
• Interfaced with other technology teams to load (Ab Initio ETL), extract and transform data from a wide variety of data sources
• Create statistical models using distributed and standalone models to build various diagnostics, predictive and prescriptive solution
• Coordinated meetings with vendors to define requirements and system interaction agreement documentation between client and vendor system
• Built daily scorecards for Anti Money Laundry taxonomy, Disclosure of Interest and Trade Surveillance using Ab - Initio Data Quality Platform (DQP), identifying major data issues to be fixed
• Collaborated with the data providers to identify Critical Data Elements, created Data-dictionaries, evaluate data quality dimensions, analyzed findings & made recommendations
• Advised senior management on fixing root causes of data errors, increasing decision making accuracy
• Collaborated with the QA team to ensure adequate testing on software, maintained quality procedures, and ensured that appropriate documentation was in place
• Prepared Business Requirement Document (BRD) and Functional Specification Document (FSD)
• Worked under Agile and Waterfall methodology to deliver projects on a timely manner
• Created use case scenarios and documented workflow and business processes

Data Scientist

Confidential - New York, NY

• Worked as a liaison between multiple teams to gather and document requirements, developed data science platform designed to cover the end - to-end Machine learning workflow: manage data, train, evaluate, and deploy models, make predictions, and monitor predictions using different machine learning methodologies like Linear Regression, T-test, Logistic Regression, Bayesian, Decision Trees, Clustering, Classification
• Participated in all phases of research including data collection, data cleaning, data mining, developing models and visualizations
• Conducting end-to-end statistical data analysis and modeling, including querying, model building, forecasting, visualization, and implementation
• Analyzed large datasets which provided strategic directions for the company
• Built quantitative model to measure the effect of customer inquiries on Bond Implied Ratings; concluded that the number of call inquiring on bond issuers is predictive of the changes in issuer's bond implied ratings
• Conducted a penetration study to evaluate the distribution of customers across 5 different industries and over 100 geographical markets; created lead lists of potential clients for sales reps
• Built quantitative models to measure the effect of Confidential 's activities and events on sales across >5,000 customers and >100 products; identified potential sales opportunities across 30% of Confidential 's clients; created profit generating opportunities through statistical analysis of client's activities and behaviors
• Created monthly dashboard to identify sales trends, best and worst performing products, website usage and changes in run rate per customer
• Created and maintained a sales database used for statistical analysis in SQL
• Automated the processing of a monthly dashboard using SQL
• Maintaining relationships with key stake holders to create products that meet the business needs

Equity Research Analyst

Confidential - Jersy city, NJ

• Developed search tools using Bloomberg to identify > 10,000 distressed companies
• Analyzed company's balance sheet, board of directors, shareholders and management, compiling reports on those that met the investment criteria
• Created and projected company financial models, compiled industry data and performed benchmarking and company competitive analysis to evaluate and recommend investment ideas
• Compiled, organized and summarized data analysis for industry publications, identifying drivers, tracking market fundamentals and comparative investment returns
• Presented findings to the senior management and made successful investment recommendations

SKILL:

Data Science, MS Excel, Python (Pandas, Numpy, Seaborn, Scipy, Matplotlib, Scikit-learn, Apriori), SQL