Pradeep Joshi Email & Phone Number

Columbia, Maryland, Us

• Worked as project lead for a Renewable Energy Source Client to build direct mail acquisition campaign strategy and optimization to maximize expected net value, campaign execution, A/B Testing, response forecasting, campaign reporting• Automatized the campaign design and selection process, saving nearly three weeks of time• Spearheaded weekly meetings with technical and business stakeholders, articulating data analysis outcomes, which fostered enhanced comprehension and informed decision-making• Developed a Media Mix Model (MMM) to accurately forecast media spending, strategically reallocating the budget towards media ads resulting in a 15% ROI increase

Columbia, Maryland, Us

• Built propensity models for better targeting and lower CPA leading to 2X mail volume growth with lowest cost of acquisition• Collaborated in developing and implementing a mixed integer programming optimization engine for generic drug pricing• Integrated improvements into the model(10K+ Decision Variables) by applying optimization to multiple previously excluded infeasibility cases, executed validation, applied sensitivity analysis leading to over 20 times improvement in the efficiency

Columbia, Maryland, Us

• Integrated Insurtech client’s data with a universal 3rd party US household database and developed customer profiling dashboards using Python and MS Excel to compare existing policy purchasers against prospects based on their demographic profile• Developed a lookalike model using logistic regression with an AUC of 77% to identify customers who are most likely to purchase Medicare using Python, R and Snowflake• Developed a DM campaign strategy to onboard best possible prospects by scoring them with the developed targeting model• Measured the KPIs and performed test of significance to measure the campaign performance between test and control group• Created 2 customer acquisition models - Retail and D2D for a Renewable Energy Source client by leveraging client data with the 3rd party demographic data to target customers in existing markets and non-existing markets • Performed aggregations at ZIP and Census tract level to identify top retail locations and geographies for D2D sales using SQL and created visualizations using Tableau

Brook Green, London, Gb

OFFER SCIENCE• Utilized text-mining (JaroWinkler, Levenshtein Distance, Fuzzywuzzy) techniques to develop attributes based on text description• Identified use cases based on customer, transaction and product level and performed Exploratory Data Analysis to understand offer distribution, menu coverage from offers and customer engagements• Calculated a Relevancy score based on recency, frequency and sales of a product for each customer-product combination• Using Naïve Bayes, a product affinity score was calculated which was then folded into the relevancy score to establish a relationship between customers and products not purchased earlier• Implemented K-means clustering to segment customers into 5 different groups based on who visit more often and spend more• Evaluated a test that was in the market for a region to check the repeat rates for customers• Worked on evaluating the performance and impact of offer attributes on individual customer in order to create an offer pool to understand offer gaps, availability of offer etc. to help create relevant offers for each customer

Brook Green, London, Gb

• Develop solutions in Python and implementing ETL process in the data warehouse and data integration project to fit the operational needs, which includes quality levels• Conduct comprehensive review of a retailer’s business & operations and identify strengths, gaps and opportunities through customer segmentation, targeting and end-to-end campaign management• Designed a template to analyze redemption/ participation/ trigger rates across different levels (customer/product/offer) at various visit patterns, which helped in improvisation for future campaigns• Identify channel of communication for promotions and target customer pool basis the probability of expected responses (using logistic regression)• Migration of legacy data and client specific business solutions from SAS to Python and to Cloud• Experience across all stages of Software Development Life Cycle (SDLC) in data warehouse and data integration project implementation in Python, PL/SQL, and UNIX Shell Scripts• Implementing ETL process in the data warehouse and data integration project to fit the operational needs, which includes quality levels

Sydney, Nsw, Au

• Worked with payments team to develop query driven model required for credit scoring thereby identifying the defaulters• Data extraction using SQL and data mining and visualization using Python and for dashboards using Tableau • Implemented automation Scripts for cache flushing of the servers

Mumbai, Maharashtra, In

Project: Shop Target: DW project for Shop Application with tools like Business Objects for reporting, Informatica for ETL and Oracle for Database. Responsibilities:• Experience across all stages of Software Development Life Cycle (SDLC) in data warehouse and data integration project implementation in Python, PL/SQL, UNIX Shell Scripts.• Implementing ETL process using Informatica in the data warehouse and data integration project to fit the operational needs.• Involved in creating Oracle PL/SQL Stored Procedures, Functions with Query optimizations as part of ETL process.• Created complex reports involving report data/measures on Business Objects Tool.• Handing BO related tickets (Universe design, Universe migration, and Performance tuning, Report Bursting, User and group management, Creating Profiles, Creating Publications).• HL/LL Documentation (Requirement Specification document).Project: Royal Bank of Scotland – SEPATarget: To support SEPA system for inter- continent of money transfer of RBS.Responsibilities:-• Implementation support on Pre-Production (QA) and Test Environments (ST/UAT/NFT) for RBS Payment Engine.• Developing Shell Scripts scheduling batch jobs as per client requirement.• Working on Oracle Wallets.• Raising CMRs (Change Management Request) using InfoMan (IBM Mainframe Tool).• Working on HP Service Automation Client to access Production/Disaster Recovery Servers.• Troubleshooting Web sphere SIB/MQ’s using SIB and HERMES tool and fixing job/batch abends.• Creating KSDs (Knowledge Solution Document) using HP Service Manager.• Performing smoke tests on Bank Visibility Application.• Invoking Batch Jobs through Mainframe Test Server which triggers the jobs in Linux Test Server. • Raising trackers in PVCS to build JCL components and to schedule batch jobs in mainframe.• Preparation of Schedule of Events (SOE) to implement patches on Production Servers.

Master Of Science - Ms | 3.8/4, Data Science

Bachelor Of Engineering (B.E.) | 9.23/10, Computer Science

High School | 92.4%, Science