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Bonduru S.

Associate Data scientist

Commitment
0/ 5
Competency
0/ 5
Reliability
0/ 5
  • Overall Experience: 6 Years  
  • Agile Software Development:
  • Algorithm Development:
  • Amazon Relational Database Service:
  • Artificial Intelligence:
  • Artificial Neural Networks:
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Bonduru S. 

Associate Data scientist

Commitment
0/5
Competency
0/5
Reliability
0/5

Time zones ready to work

  • Eastern Daylight [UTC -4]
  • Pacific Daylight [UTC -7]
  • Eastern European [UTC +2]
  • Greenwich Mean [UTC ±0]
  • Australian EDT [UTC +11]
  • Dubai [UTC +4]
  • New Delhi [UTC +5]
  • China (West) [UTC +6]
  • Singapore [UTC +7]
  • Hong Kong (East China) [UTC +8]

Willing to travel to client location: Yes  

About Me 

Around 6 years of experience of software industry and 3 years of rich experience across multiple technologies consisting of Python, Big Data Hadoop, Machine Learning, Dee
Around 6 years of experience of software industry and 3 years of rich experience across multiple technologies consisting of Python, Big Data Hadoop, Machine Learning, Deep Learning, Neural Networks, Predictive analytics, data visualization. Good applied statistics skills, and clear understanding of Deep Learning techniques like Recurrent Neural Networks, Text Mining using Natural Language Processing NLP, Machine Learning algorithms, such as K-Means, PCA, SVM, xgboost algorithm, Linear, Random Forests, Market Basket Analysis. Experienced in handling unstructured data like text as well as structured data, , BSON dump from MongoDB, Parquet file.
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Portfolios

Fares

Website Link:

Role:

The responsibility of this team was to develop low fares for airline systems. There are two systems set up for the interchange of fares data—ATPCO and SITA, plus some system to system direct connects. This system distributes the fare tariffs and rule sets to al

The responsibility of this team was to develop low fares for airline systems. There are two systems set up for the interchange of fares data—ATPCO and SITA, plus some system to system direct connects. This system distributes the fare tariffs and rule sets to all GDSs and other subscribers.Inventory control is typically manipulated from here, using availability feeds to open and close classes of service. Fares & Rules assembles the different fare and fare-related data fromairlines and distributes them to the different global distribution systems (GDS), revenue management and revenue accounting systems, passenger service systems, and companies who want to benefit from valuable, comprehensive data. And it does this in an industry-standard format—from onesingle source

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Skills: ProLogPython

Tools: PutttyVisual Studio Online

UCSD Express for Big Data

Website Link:

Role:

The responsibility of this team was to develop framework for Cisco UCS Director Express for Bigg Data provides a single-touch solution that automat Hadoop deployment on the Cisco UCS Common Platform Architecture (CPA) for Big Data infrastructure. It also provides a single management pane across b

The responsibility of this team was to develop framework for Cisco UCS Director Express for Bigg Data provides a single-touch solution that automat Hadoop deployment on the Cisco UCS Common Platform Architecture (CPA) for Big Data infrastructure. It also provides a single management pane across both physical infrastructure and Hadoop software. All elements of the infrastructure are handled automatically with little user inputs

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Skills: C++

Tools: VimVisual Studio Online

Cat6k Terminator 2 platform Development and Sustaining

Website Link:

Role:

IOS(Inter network Operating System) is the operating system used in various switches and other products of CISCO. The Catalyst 6500 that works on IOS has become a flagship switch for enterprise network. The new Catalyst 6500, deployed with Supervisor Engine 2T(Sup2t) in a Virtual Switching System

IOS(Inter network Operating System) is the operating system used in various switches and other products of CISCO. The Catalyst 6500 that works on IOS has become a flagship switch for enterprise network. The new Catalyst 6500, deployed with Supervisor Engine 2T(Sup2t) in a Virtual Switching System, scales existing chassis infrastructure to 4Tbps while delivering best-in-class feature sets -- including over 200 new features.

The project is intended to the sustenance and feature development of IOS control plane for Catalyst 6500’s Supervisor-720, Supervisor 2T, Terminator and Transformer platforms which includes module bring up, environment monitoring, data path init etc

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Skills: C LanguageLinux

Tools: Visual Studio Online

Employment

Lead Engineer

2013/04 - 2017/08

Skills: C LanguageC++Linux

Your Role and Responsibilities:

Ø  Code Enhancement for new features.

Ø  Handling of Customer Issues and technical meetings.

 

Ø  Code Enhancement for new features.

Ø  Handling of Customer Issues and technical meetings.

 

Associate Data scientist

2019/02 - 2019/06

Skills: PythonBig DataHadoopMachine LearningDeep LearningNeural NetworksData VisualizationNatural Language ProcessingK-means ClusteringSupport Vector Machines - (SVM)Spring Tool SuiteMongoDB

Your Role and Responsibilities:

Performed Data cleaning, transformation, validation with the purpose of understanding or making conclusions from the data for decision-making purposes, Feature extraction and feature engineering. Assist other team members in the identification and resolution of data issues that are impacting operati
Performed Data cleaning, transformation, validation with the purpose of understanding or making conclusions from the data for decision-making purposes, Feature extraction and feature engineering. Assist other team members in the identification and resolution of data issues that are impacting operation performance. Build the various suitable model and integrating Analytics capabilities to run data classification, and clustering using deep learning model. After building the model, do a model evaluation metric with multiple approaches. Update the status to a higher person and client while in the meeting. Deploy the in various stages like UAT, pre-production, and production. Solved environmental issue while deploying. Once the deployment is completed and will monitor the model prediction with live data. Based on the prediction fine-tune the hyperparameter to the model.
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Associate Data scientist

2018/06 - 2018/12

Skills: PythonBig DataHadoopMachine LearningDeep LearningNeural NetworksData VisualizationNatural Language ProcessingK-means ClusteringSupport Vector Machines - (SVM)Spring Tool SuiteMongoDB

Your Role and Responsibilities:

Understanding the domain part closely with Business Analyst. Extracting the feature from text data using NLP and regular expression. Build deep learning model for the output of text data in vectorization format. After building the model, do a model evaluation metric with multiple approaches. Update
Understanding the domain part closely with Business Analyst. Extracting the feature from text data using NLP and regular expression. Build deep learning model for the output of text data in vectorization format. After building the model, do a model evaluation metric with multiple approaches. Update the status to a higher person and client while in the meeting. Deploy the in various stages like UAT, pre-production, and production. Solved environmental issue while deploying. Once the deployment is completed and will monitor the model prediction with live data. Based on the prediction fine-tune the hyperparameter to the model.
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Lead Engineer

2017/01 - 2018/08

Skills: PythonBig DataHadoopMachine LearningDeep LearningNeural NetworksData VisualizationNatural Language ProcessingK-means ClusteringSupport Vector Machines - (SVM)Spring Tool SuiteMongoDB

Your Role and Responsibilities:

Understanding the domain part closely with Business Analyst. Transforming the data into various stages like data cleaning, normalization, and transformation the data into usable data sets that can be analyzed to extract insights and improve business processes. Identification and resolution of data l
Understanding the domain part closely with Business Analyst. Transforming the data into various stages like data cleaning, normalization, and transformation the data into usable data sets that can be analyzed to extract insights and improve business processes. Identification and resolution of data level issues that are impacting operation performance. Data level analysis is done using the statical approach. Update the status to a higher person and client while in the meeting. Deployed in various stages like UAT, pre-production, and production.
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Education

2007 - 2011

2011 - 2011

Skills

Agile Software Development Algorithm Development Amazon Relational Database Service Artificial Intelligence Artificial Neural Networks
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Tools

Visual Studio Online

Hobbies

Travelling

Reading books

Music

Achievements

Ø  Appreciated two times with SPARC award.

Awarded with productivity champion award for quick and quality of bug fixing

Preferred Languages

English - Conversational