PROFILE SUMMARY:

• Results - driven, dedicated, and accomplished Software Engineer around 13 years track record of developing and implementing customized software solutions for various technologies with a strong interest and background in AI, NN, ML & Big Data infrastructures and resolving complex issues involving large scale data, analytics, statistical data analysis and reporting.
• Analytics professional with the ability to effectively evaluate and process structured and unstructured data.
• Highly skilled at project management, successfully planning, executing, and completing projects to align with business needs.
• Recognized leader capable of leading and motivating team members to meet and exceed organizational and individual goals.
• Excellent interpersonal skills used to interact and cultivate long-term business relationships with stakeholders, associate, senior leaders and clients.
• Having a very high level concepts in Graph Theory including Graph ADT, Graph Data Structure{Edge List, Adjacency List, Adjacency Map, Adjacency Matrix} along with the implementation of Graph concept in Graph Database ‘Neo4J’ by the following algorithms including, PageRank, Centrality Algorithm(Betweenness, Closeness and Harmonic), Shortest Path Single Source, Yen’s K-shortest, All PairsA* Algorithm & others.

SOME DETAILS IN TECHNICAL AND DOMAIN PROFICIENCY:

High-Level Language: ShellScript (Using awk, sed, grep), rsync, openssl, XML, XSLT, NVDL, JavaScript(including D3JS, techanJS), VBA, R-Programing, Python 3.5/3.7, Advanced Excel, Power Query, Power BI, Excel Get & Transform. REST-API programming using JAVA-JERSEY, Python-FLASK and PHP. Algorithmic Trading using Python utility Zipline, PyAlgoTrade. Web Scraping & Crawling using Python utility Scrapy, BeautifulSoup & PHP-CURL.

Databases/Structures Methodology: SQL Server, Oracle, MySQL, Derby. MongoDB concept in Aggregation Pipeline including Pipeline Sequence Optimization Pipeline Coalescence Optimization, Map-Reduce, Storage Engine{WiredTiger(default from ver- 3.2), MMAPv1, In Memory}. GridFS, Sharding & indexing . BigChainDB-v-1.2 Python API for blockchain datastore configured with MongoDB- 3.2 to 4.0 .

Other Tools/Frameworks Algorithm Concepts: Hadoop Apache & Cloudera Distribution, Microsoft Azure HDInsight, Hive Data storing in TEXTFILE / SEQUENCEFILE / RCFILE /ORCFILE, along with partitioning, bucketing, indexing using HiveQL and joining concepts like Reduce side, Map Side and Bucketed join, Statistical Framework R Data -- Import, Quality, Manipulation, Analysis and Visualization, D3JS v-3, v-4, v-5 Excel Power BI, Power Query with DAX, Optimization techniques using Excel Solver, Analysis. Decision Tree designing in excel. R packages (quantmod, TTR, xts) for Stock quote, stock market data analysis, stock chart analysis(candlestick, OHLC, Bar Chart).

EMPLOYERS:

Confidential

Senior Associate

Confidential

Senior Software Engineer

Confidential

Sr. Software Engr

Confidential

Software Engineer

Responsibilities:

• Live project exposure in Hadoop Cloudera, Azure HDInsight Distribution and Hive and PIG script for data processing for report generation, focusing on ETL/ELT functionality.
• Working exposure in the statistical programming language R-programming, Advanced MS Excel, Power Query, Power BI, VBA & D3JS(ver-3, ver-4, ver-5), techanJS.
• Hands on exposure in Regression Analysis Linear, Multiple, Logistic, Multinomial and Ordinal Logistic and Log-Linear along with distributions and statistical methods & Machine Learning.
• Hands on exposure using open source machine learning tools for Supervised Generalized Linear Model, Gradient Boosting Machine, Deep Learning, Naïve Bayes, Distributed Random Forest etc., Unsupervised Generalized Low Ranking Model, K-Means, Principal Component Analysis .
• Exposure using multiple SQL platforms. Exposure in Document database MongoDB 3.2 to 4.0 .
• Hands on concept using Graph Database Neo4J v-3.4.0 using cypher-shell and neo4j console.
• Experience with UNIX/Linux based system, app admin using BASH/KSH awk, sed, grep, rsync, opnssl .
• Exposure in Python 3.5/3.7 Lambda and Comprehension, Decorators, Context Managers, Iterators & Generators, Functools & Itertools, Data Classes .
• Hands On Exposure in Python based NLP utility spaCy, NLTK, TextBlob.
• Hands on exposure in Python based Data Science Libraries like sci-kit, pandas, numpy, matplotlib.
• Hands on exposure in Machine/Deep Learning Library KERAS/TensorFlow and PyTorch, PyOpenCV.
• Hands on exposure in Neural Network CNN, RNN etc. using the activation functions like Sigmoid, Softmax, Tanh or ReLU Rectified Linear Unit for Feed Forward Network 1.Single Layer Perceptron, 2.Multi Layer Perceptron with Input, Hidden and Output Nodes.
• Hands on exposure and theoretical ideas in Gradient Descent variants like 1. Batch Gradient, 2. Mini-Batch Gradient, 3. Stochastic Gradient Descent and optimization algorithm like Momentum, Nesterov Accelerated Gradient, Adagrad, Adadelta, RMSProp. Adam, AdaMax, Nadam, AMSGrad .
• Hands on exposure on Time Series Analysis including, Forecasting Accuracy using Diebold Mariano, Pesaran-Timmerman Test, Simple Moving Average, Weighted Moving Average, Simple Exponential Smoothing, Holt’s Linear Trend, Holt-Winter’s Method; Stochastic processes like Stationary Process, Auto Correlation Function ACF, Partial ACF, Purely Random Time Series(White-noise), Random Walk, Auto Regressive Process, Moving Average Process, Auto Regressive Moving Average{ARMA(1,1), ARMA(p,q)}, Auto Regressive Integrated Moving Average(ARIMA).
• Some basic hands on activity using ElasticSearch, LogStash, Kibana and its corresponding Python utility.
• Exposure and understanding in different use cases like ISO-8583 message structure, Barcode symbologies, GS1 standard for identifying, capturing and sharing business information.
• Working exposure in Market Data for American OPTIONS for equities traded in US stock exchanges like NYSE, NASDAQ, AMEX etc. Also including Binary, European and other types of OPTIONS.
• Project Lifecycle wise activity exposures in Requirement Analysis & Technical Specification, Data Analysis, Collection & Warehousing, Testing Services. Exposure in both SDLC & Agile.
• Project Management wise activity exposure in Process Improvement, Team Leadership, & Development, Mentorship.