Be accountable for building and delivering AWS and/or Azure Cloud Platforms infrastructure and solutions to help your clients meet the soaring data and cloud demands of AI and machine learning, IoT, advanced analytics, open source and other emerging digital technologies.

More Uses of the Big Data Analytics Toolkit:

  • Develop, maintain, and continuously improve customer churn, customer acquisition, and customer value models to inform go to market strategy and drive improved profitability.
  • Develop, maintain, and continuously improve media mix modeling, mass media attribution, multi touch attribution, and other models to support the optimization of marketing spend.
  • Ensure you cloud architecture, design and development that supports diagnostic instruments, with a focus on data architecture, Big Data Analytics, microservices, and database services.
  • Lead: independently develop customized algorithms to solve analytical problems with incomplete data sets and implements automated processes for efficiently producing scale models.
  • Manage it security and data governance to ensure that your organizations data analytics and integration products are effectively secured and that risks are mitigated.
  • Become a data expert, utilizing the data warehouse to inform modeling approaches, understand customer behavior, research outliers, and prepare data for usage by the quantitative modeling team.
  • Secure your organization provides support by mining data to identify behavior patterns, predict trends, and forecast outcomes to support data driven decisions to drive change in your customer interactions and risk management.
  • Direct: partner with business development and account management teams in helping to ensure customer success in building and migrating applications, software and services on the aws platform.
  • Devise strategy and engage with solution architects, account managers, professional services and partners to define a database and analytics engagement strategy for aws key accounts.
  • Be accountable for working closely with the various teams data science, database, network, BI and application teams to make sure that all the big data applications are highly available and performing as expected.
  • Manage work with application management team, and where necessary, other members of the analytics team to efficiently execute larger scale analytic deliverables and operationalize the results.
  • Provide technology agnostic technical leadership, drive technology stack selection and ensure the project team is setup for success on any number of open source, commercial, on premise and/or cloud based data engineering technologies.
  • Recognize and drive opportunities to lead technical considerations in designing Data lakes, Data warehouses, IT operations analytics based on Machine learning methodologies, and similar large scale Data products.
  • Be accountable for designing, architecting, and developing solutions leveraging big data technology (open source, aws, or microsoft) to ingest, process and analyze large, disparate data sets to exceed business requirements.
  • Orchestrate: behavioral classification, forecasting and prediction, fusion of multiple data sources, or in general improving your current algorithm by more sophisticated data driving models.
  • Make sure that your organization serves as a resource to advise management and business stakeholders on use of quality business analytics, tools, and methods to improve efficiency, accuracy, and interpretation of various business metrics.
  • Manage work with client management team and your customers to define and take ownership of scope, intermediate deliverables, and timelines around larger scale analytic deliverables.
  • Promote technical readiness and capability of database and analytics services by driving organizational initiatives across multiple geographies to develop and share best practices.
  • Develop productive relationships with Business Unit leaders across your organization to influence how data integration technology solutions can enable new sources of value.
  • Identify recurring problems and bottlenecks that might be improved through upgrades to your software product, new technologies in the analytics team infrastructure, or further research into statistical methodology.
  • Manage work with large structured / unstructured data sets, various rest/wms data services, multiple database programs and collection systems, in a modeling and analytical environment, solving hard intelligence problems and issues.
  • Ensure you lead development of custom predictive and prescriptive algorithms interfacing with large data sets, based on principles from statistics, machine learning, and operations research.
  • Engage to architect and design for your customers data driven applications, and drive the evolution of the AWS Services by innovating around capabilities like Advanced analytics, Machine learning, and Serverless.
  • Collaborate with your customer, partners, and AWS engineering teams to solve for enterprise problems like Database Migrations, Data warehousing, Real time analytics, Operational analytics, and Big data processing on the cloud.
  • Be accountable for ensuring highly available, secure, and compliant infrastructure to cost effectively support all your business critical needs, whether in on premise, cloud/multi cloud, or hybrid deployments.

 

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