Go beyond the expected

Cyber Security

Cybersecurity is fast shaping up to be one of the most important careers in the modern workplace. Cybersecurity involves the protection of electronic data, be it on websites, databases, networks, devices, or, increasingly, the cloud. Cybersecurity professionals use advanced technological systems and computer science knowledge to keep your data safe and secure.

  • FOCUS AREAS
  • RECENT PROJECTS
  • SKILLS
  • CERTIFICATIONS
    • Governance, Risk and Compliance
    • Data Loss Prevention
    • Cloud Security
    • Network & Endpoint Security
    • Cryptography and Public Key Infrastructure
    • Security Monitoring & Incident Handling
    • Threat Intelligence
    • Vulnerability Management
    • Identity & Access Management
    • Security Operations
  • • Implementation and support of the Enterprise Privilege Vault Management System (EPVM) Platform.

    • Design, deployment, configuration and maintenance of CyberArk PIM Suite in a global environment.

    • GSOC operators monitor paid, open, and social intelligence feeds for security incidents and disasters with the potential to create business disruptions globally.

    • Worked closely with Infrastructure, Application, Network, Security, and Business Intelligence teams getting started with Splunk.

    • Grow and improve the enterprise Splunk environment from early stages to a mature implementation by creating forwarder apps to ingest data.

    • Identifying and securing the enterprise's information assets through assessing risk associated with suppliers doing business with Client.

    • Worked with Client’s Identity and Access Management Team for decoding scripts and workflows from a legacy NetIQ environment in support of transition to SailPoint.

    • CyberArk
    • Ping Federate
    • Ping Access
    • Ping ID
    • SAML
    • OAUTH federation
    • ArcherGRC
    • RiskLens
    • AWS
    • Azure
    • GCP
    • GIAC
    • CISSP
    • CRISC
    • CISM
    • CCIE Security
    • CompTIA
    • Microsoft
    • EC-Council
    • ISACA
    • ISC2
    • SANS Institute/GIAC
    • PCIP
    • CEH
    • GCIH
    • CCP

DevOps and Cloud Computing

People, Process, Technology—the job of a DevOps specialist is to bring these three elements together in order to create efficient product development processes. DevOps (a composite of Development and Operations) brings together otherwise siloed organizational departments such as development, IT, quality control, and security engineering, to create more collaborative product development strategies.

  • FOCUS AREAS
  • RECENT PROJECTS
  • SKILLS
  • CLOUD PLATFORMS
    • Assessment and Planning
    • Pilot Framework Creation
    • Process Implementation
    • CI/CD Pipeline
    • Process Automation
    • Security Integration
  • • Migration of Service and applications from On-Prem to AWS Cloud: Team worked on migrating a complex heterogeneous portfolio of application and backend services from on-prem to AWS cloud. It involved rewriting of required services and application components along with the migration of systems and setting up CI/CD and cloud watch monitoring dashboards. The majority of the systems were containerized using Docker for migration to AWS Elastic Container service.

    • Migration of Hadoop cluster to AWS EMR: This project involved the migration of the on-prem Hadoop cluster to AWS EMR and building additional Big data processing jobs using PySpark on AWS EMR.

    • Build Data Lake on Google Cloud Platform: This project involved the migration of ETL jobs and Data storage from on-prem Data warehouse built on Teradata to a Data Lake solution using Google Storage and Google Bigquery.

    • Python
    • Hadoop
    • R
    • Spark
    • Scala
    • Perl
    • Matlab
    • Java
    • C
    • SQL
    • Postgres SQL
    • Hive
    • Pig
    • Scala
    • AWS
    • GCP
    • Azure
    • JSON
    • YAML
    • XML
    • PHP
    • Amazon Web Services (AWS)
    • Microsoft Azure
    • Google Cloud Platform (GCP)
    • Openstack

Data Science

Data science is one of the most exciting new fields out there today.

Data scientists develop processes that can identify and extract key information from large amounts of data, which organizations can leverage to spot trends, make better decisions, and develop prediction models. Data science also enables machine learning models to learn from large amounts of data, making them smarter and more capable of automation and assistance.

  • FOCUS AREAS
  • RECENT PROJECTS
  • SKILLS
  • ALGORITHMS
    • Diagnostic
    • Prescriptive
    • Descriptive
    • Classification and Predictive
    • Deep Analytics
    • Advanced Data Modeling
  • • Build Dynamic Pricing for Ecommerce Channel: Team worked on building a rule based dynamic pricing engine which used competitor price data along with other data matrices like margin, inventory, cost etc. to change price of products in real time to remain competitive.

    • Migration of Hadoop Cluster to AWS EMR: This project involved migration of on premise Hadoop cluster to AWS EMR and building additional Big data processing jobs using PySpark on AWS EMR.

    • Build Data Lake on Google Cloud Platform: This project involved migration of ETL jobs and Data storage from on prem Data warehouse built on Teradata to a Data Lake solution using Google Storage and Google Bigquery.

    • Build Clearance pricing application for Markdown Management: This project involved building a new front end interface using Angular js and node js as well as backend services using Spring Boot and MySQL DB. The backend processing for the system was implemented using micro services and Kafka technologies.

    • Build Pricing and Promo Optimization Machine Learning Models: Team worked on building and deploying highly scalable machine learning models for clearance and promotional price optimization. The solution was built using Python, PySpark, Pig and Hive.

    • Python
    • Hadoop
    • R
    • Spark
    • Scala
    • Perl
    • Matla
    • Java
    • C
    • SQL
    • Postgres SQL
    • Hive
    • Pig
    • Scal
    • AWS
    • GCP
    • Azure
    • JSON
    • YAML
    • XML
    • PHP
    • Regression
    • Classification
    • Decision Trees
    • Bayesian
    • Clustering
    • CNN
    • LSTM
    • Text Mining
    • SVM
    • RF
    • XGBOOST
    • Time series modeling
    • Dimensionality reduction
    • SEM
    • GLM
    • GLMM
    • Clustering
    • Neural Networks / Deep Learning / Natural Language Processing (NLP)
    • Neural Networks

AI/ML

The wealth of data that is being generated by consumers today have made Machine Learning (ML) and Artificial Intelligence (AI) key scientific tools for modern business.

AI is a branch of computer science which focuses on building intelligent machines which can use deep learning and natural language processing to automate functions that would otherwise require human beings.

ML is a subset of AI that uses large amounts of data and algorithmic programming to learn and perform tasks independent or semi-independent of human supervision.

AI is employed in many different industries like from healthcare to transportation. Chatbots, AI recruiting platforms, e-commerce and retail assistants—many day-to-day customers service operations can be automated and performed with ML and AI.

  • FOCUS AREAS
  • RECENT PROJECTS
  • SKILLS
  • ALGORITHMS
26+ Years in IT Placements & Staffing Solutions

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