Strategy & Analytics
Strategy
Our Strategy practice brings together several key capabilities that will allow us to architect integrated programs that transform our clients’ businesses, including Corporate & Business Unit Strategy, Technology Strategy & Insights, Enterprise Model Design, Enterprise Cloud Strategy and Business Transformation.
Strategy professionals will serve as trusted advisors to our clients, working with them to make clear data-driven choices about where to play and how to win, in order to drive growth and enterprise value.
Strategy will help our clients:
• Identify strategies for growth and value creation
• Develop the appropriate business models, operating models, and capabilities to support their strategic vision
• Maximize the ROI on technology investments and leverage technology and Cloud trends to architect future business strategies
Analytics & Cognitive
In this age of disruption, organizations need to navigate the future with confidence, embracing decision making with clear, data-driven choices that deliver enterprise value in a dynamic business environment.
The Analytics & Cognitive team leverages the power of data, analytics, robotics, science and cognitive technologies to uncover hidden relationships from vast troves of data, generate insights, and inform decision-making. Together with the Strategy practice, our Strategy & Analytics portfolio helps clients transform their business by architecting organizational intelligence programs and differentiated strategies to win in their chosen markets.
Analytics & Cognitive will work with our clients to:
• Implement large-scale data ecosystems including data management, governance and the integration of structured and unstructured data to generate insights leveraging cloud-based platforms
• Leverage automation, cognitive and science-based techniques to manage data, predict scenarios and prescribe actions
• Drive operational efficiency by maintaining their data ecosystems, sourcing analytics expertise and providing As-a-Service offerings for continuous insights and improvements
ML OPs Engineer
Required:
• 6-10 years of Consulting, Data, and Analytics experience
• Experience in descriptive & predictive analytics, both theoretical and practical knowledge in basic ML algorithms like linear and non-linear regression, linear and non-linear classification, dimensional reduction, anomaly detection, statistical concepts and techniques like theoretical distributions, parametric and non-parametric inference
• 6+ years of experience implementing & executing data science projects throughout the entire lifecycle: Developing/designing and implementing solutions E2E in production.
• Strong knowledge of Python or R
• Programming experience with Node.js, SQL, Java, JavaScript OR PERL
• Experience in cloud-based data platforms on AWS, GCP and Azure
• Understanding of multi-tier application architectures
• Ability to develop, test and maintain programming environments and architectural standards
• Foundational understanding of application development lifecycle and using tools like ANT, Maven, Gradle and Version control (SVN OR GIT OR BitBucket)
• Experience with working in an agile development lifecycle and continuous integration processes using tools such as Jenkins
• Experience in doing deployments for Java, .NET , Angular , Node.js , PHP, Python applications using Jenkins/Bamboo
• Experience on code quality assessment tools and integration with CI tool
• Strong logical structuring and problem-solving skills
• Strong verbal, written and presentation skills
Preferred Additional
• Experience in using Spark either with Scala or Python
• Experience with different database types like RDS and NoSQL
• Experience in cloud deployments
• Knowledge of working in a Linux environment
• Strong understanding and experience configuring, managing and supporting applications using tools such as OpsWorks, Datadog and CloudWatch on AWS
• Experience in Docker /Swarm / Kubernetes
• Experience or exposure to Test Driven Development Experience (Junit / TestNG)
• Experience on Behavior Driven Development Experience (Cucumber / Selenium)
• Expertise in any commercial data visualization tool such as Tableau, Qlik, Power BI
• Experience with real time data movement solutions that use security and encryption protocols while data is in transit
Strategy & Analytics
Strategy
Our Strategy practice brings together several key capabilities that will allow us to architect integrated programs that transform our clients’ businesses, including Corporate & Business Unit Strategy, Technology Strategy & Insights, Enterprise Model Design, Enterprise Cloud Strategy and Business Transformation.
Strategy professionals will serve as trusted advisors to our clients, working with them to make clear data-driven choices about where to play and how to win, in order to drive growth and enterprise value.
Strategy will help our clients:
• Identify strategies for growth and value creation
• Develop the appropriate business models, operating models, and capabilities to support their strategic vision
• Maximize the ROI on technology investments and leverage technology and Cloud trends to architect future business strategies
Analytics & Cognitive
In this age of disruption, organizations need to navigate the future with confidence, embracing decision making with clear, data-driven choices that deliver enterprise value in a dynamic business environment.
The Analytics & Cognitive team leverages the power of data, analytics, robotics, science and cognitive technologies to uncover hidden relationships from vast troves of data, generate insights, and inform decision-making. Together with the Strategy practice, our Strategy & Analytics portfolio helps clients transform their business by architecting organizational intelligence programs and differentiated strategies to win in their chosen markets.
Analytics & Cognitive will work with our clients to:
• Implement large-scale data ecosystems including data management, governance and the integration of structured and unstructured data to generate insights leveraging cloud-based platforms
• Leverage automation, cognitive and science-based techniques to manage data, predict scenarios and prescribe actions
• Drive operational efficiency by maintaining their data ecosystems, sourcing analytics expertise and providing As-a-Service offerings for continuous insights and improvements
ML OPs Engineer
Required:
• 6-10 years of Consulting, Data, and Analytics experience
• Experience in descriptive & predictive analytics, both theoretical and practical knowledge in basic ML algorithms like linear and non-linear regression, linear and non-linear classification, dimensional reduction, anomaly detection, statistical concepts and techniques like theoretical distributions, parametric and non-parametric inference
• 6+ years of experience implementing & executing data science projects throughout the entire lifecycle: Developing/designing and implementing solutions E2E in production.
• Strong knowledge of Python or R
• Programming experience with Node.js, SQL, Java, JavaScript OR PERL
• Experience in cloud-based data platforms on AWS, GCP and Azure
• Understanding of multi-tier application architectures
• Ability to develop, test and maintain programming environments and architectural standards
• Foundational understanding of application development lifecycle and using tools like ANT, Maven, Gradle and Version control (SVN OR GIT OR BitBucket)
• Experience with working in an agile development lifecycle and continuous integration processes using tools such as Jenkins
• Experience in doing deployments for Java, .NET , Angular , Node.js , PHP, Python applications using Jenkins/Bamboo
• Experience on code quality assessment tools and integration with CI tool
• Strong logical structuring and problem-solving skills
• Strong verbal, written and presentation skills
Preferred Additional
• Experience in using Spark either with Scala or Python
• Experience with different database types like RDS and NoSQL
• Experience in cloud deployments
• Knowledge of working in a Linux environment
• Strong understanding and experience configuring, managing and supporting applications using tools such as OpsWorks, Datadog and CloudWatch on AWS
• Experience in Docker /Swarm / Kubernetes
• Experience or exposure to Test Driven Development Experience (Junit / TestNG)
• Experience on Behavior Driven Development Experience (Cucumber / Selenium)
• Expertise in any commercial data visualization tool such as Tableau, Qlik, Power BI
• Experience with real time data movement solutions that use security and encryption protocols while data is in transit