Lead Data Science Resume

SUMMARY

Led teams of sizes 3 - 10 people (onsite and offshore) providing though leadership, modeling and mentorship to more than 10 projects.
Built many customer and business centric dashboards to answer key client questions, monitor models, produce analysis results using Tableau and QuickSight.
Conducted workshops on Docker, AWS Sagemaker, GPU processing; and weekly ML strategy review sessions to team members that include MS and PhD Data Scientists.
Certified AWS developer having experience to architect and implement solutions in AWS solutions such as EC2, S3, Glacier, lambda, Athena, Glue, RDS, Redshift, Sagemaker, Aurora, EMR, Quicksight, etc.
Built ML models such as forecasting model, risk models, classification, fault prediction, next product to buy, rule based models, sentiment analysis, propensity models, etc.
Experience extracting data from Big Data bases such as MySQL, Hadoop, MariaDB, PrestoDB, Hive, Kafka, Elastic Search.
Worked closely with business, data governance, SMEs and vendors to define data requirements.
Built models using LSTM, Neural Nets with keras on Tensor Flow, MinMax, HMM, logistic regressions, Random Forests, SVM, k-NN, time series models using packages such as ggplot, dplyr, numpy, sci-kit learn, pandas, matplotlib, etc.
Automated by building workflows to extract data from various REST APIs and databases, processing responses, data transformations in python and R.
Reported analytical findings to C-level executives using dashboards built in Splunk, Tableau, Qlik View, R-Shiny.
Managed teams to perform data analysis on classification and forecast models, statistical models, risk analysis and solved data driven problems using SPSS, SAS E-Miner, R, SAS, Python, E-Views, Tableau, Qlik.

TECHNICAL SKILLS

PROGRAMMING LANGUAGES: Python, R, SAS, C, Matlab, Java, SQL, Hive, Linux, VBA Macro, Linux, HTML, CSS, JavaScript, and Bootstrap.

TOOLS: & DATABASES: RStudio, python, Spark, AWS, SPSS, SAS, Hadoop, Hive, MongoDB, Cassendra, Zeppelin, S3, Aurora, Glacier, Elastic Search, EC2, Lambda, Quick Sight, Splunk, Tableau, Qlik, Adobe Site Catalyst, Google Analytics, MS Visual Studio, Excel, MS PowerPoint.

PROFESSIONAL EXPERIENCE

Confidential

Lead Data Science

Responsibilities:

Manage ad-hoc analytical requests from Flights, hotels, cars stake holders.
Implemented end-to-end CICD enabled platform using AWS Sagemaker to deploy models to production at scale.
Add ML model improvements and new feature additions to Krazyglue (LOB recommendation engine of Confidential ) and perform ML model improvements using deep learning techniques.
Collaborate with UI and engineering team for new ML feature roll-outs and orchestrate AB testing to report and track performance.
Find answers to key business questions by building complex queries in Hive on Hadoop, Teradata.
Analyze website traffic data to Brand Confidential, Hotels, Hotwire, Travelvelocity, Orbitz, trivago websites and generate dashboards in Adobe Analytics.

Tools: Python, pyspark, Hadoop, Teradata, HiveQL, Tableau, AWS EC2, SageMaker, Aurora, QuickSight, PowerBI.

Confidential

Lead Data Scientist

Responsibilities:

Extracted inventory flow and stock level data across various nodes (hubs, stores, etc) by joining tables from more than 10 databases.
Assessed the scope and scale of project based on current and future scope of project.
Implemented hybrid architecture using Hive, PrestoDB, MariaDB, AWS Aurora, S3, Glacier, Spark, EMR.
Forecasted Average weekly demand using historical demand data and calculated safety stock, cycle stock and max stock across all nodes (Hubs, stores, etc) based on predictions.
Built MinMax, LSTM, ARIMA machine learning & deep learning models and sent results back to local databases.
Build Tableau dashboards for ad-hoc analysis and to compare results.

Tools: AWS Aurora, S3, Glacier, EMR, Python, PySpark, Rest API, Linux, Hive, PrestoDB, MariaDB, Tableau.

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