Let us do the heavy lifting and deliver the entire project for you!
TalentSumo powered solutions provide support for frontier technologies where the talent is not readily available. We provide end to end project-based support with a flexible onsite-offshore model as required. We provide industry-specific use-case driven talent teams who can deliver smart proof of concept to enterprise-wide implementations in the following niche technology areas:
BlockChain and IoT solutions:
• Design and build industry-specific solutions using the Blockchain technology
• Contribute to infrastructure setup and solution development in Blockchain and related technologies such as Ethereum, cryptocurrencies and smart contracts.
• Understand functional requirements as applicable to various industries and convert into system specifications for development.
• Define development approach and best practices to implement the solutions.
• Design and build Blockchain framework, accelerators, and assets.
• Document development artifacts and best practices.
• Mentor team members, review code artifacts and provide technical guidance
Data Science & Artificial Intelligence:
• Function as a predictive modeling expert or application team leads on internal and customer-facing external projects.Practical experience at large scale in one or more of the following domains: natural language processing, machine learning, search, information retrieval or text classification
• Solid experience in Java, Python, Scala, or another object-oriented language
• Expertise with ML/NLP frameworks such as sci-kit-learn, Weka, Pandas, Mallet, TensorFlow, PyTorch, Theano
• Build and test analytic and statistical models to improve a wide variety of both internal data-driven processes for map-building and external, customer-facing automated decision and system control needs.
• Design and analyze A/B experiments that validate different optimization and predictive scoring solutions and/or calibrate predictive model parameters.
• Act as an expert and evangelist in areas of data mining, machine learning and deep learning, statistics, and predictive analysis and modeling.
Big Data Engineering :
• Build and support scalable and durable data solutions that can enable self-service advanced analytics using both traditional (SQL server) and modern DW technologies (Hadoop, Spark, Cloud, NoSQL etc.) in an agile manner
• Participate in all aspects of the software lifecycle, including analysis, design, development, unit testing, production deployment, and support
• Capable of working closely with business and product teams to ensure data solutions are aligned with business initiatives and are of high quality
• Collaborate and validate implementation with Data Analytics team and other technical team members.
• Ensure that the platform goes through Continuous Integration (CI) and Continuous Deployment (CD) with DevOps automation
• Create Big Data accelerators to help deploy scalable solutions fast.
Cloud solutions ( Oracle, SAP, Salesforce):
- Experience implementing hybrid cloud strategies using the public cloud e.g AWS, Azure etc.
- Excellent understanding of both monolithic/legacy application architects as well as modern cloud-native application architectures Understanding of SOA, ROA, microservices and RESTful architectures.
- Excellent and clear communication and presentation skills with the ability to explain complex concepts in simpler language.
- Deep understanding of cloud architecture principles including SaaS, PaaS, IaaS, SDLC environments, multi-tenancy, security, monitoring and management, multi-tiered infrastructure, databases, integration, mobile and application servers etc.
- Experience with emerging cloud technologies (OpenStack, Docker, Mesos, Kubernetes) A good understanding of the security processes, standards & issues involved with running workloads in the public cloud Architectural and development experience of Web Services Principals of network, application and information security Industry knowledge of Financial Services, Communications and Healthcare etc a plus Experience with public cloud AWS, Azure, SoftLayer, GCE, Rackspace, Oracle