Job Title :Analytics Designer - Machine Learning, Big data & Cloud
Total IT Experience (in Yrs.)5+
Relevant Experience Required (in Yrs.)3+years of experience as senior developer with hands-on experience in Python delivering products or solutions that utilized Machine learning, Natural Language processing or other forms of AI solutions (Computer Vision/ Mathematical Optimization)
3+ years of experience working on cloud platforms - Public Cloud Platforms like AWS/Azure/GCP
4+ years of experience in working and deep understanding of Apache Hadoop and the Hadoop ecosystem
Language Requirement English.
Python, Spark, HDFS, Hive, HBase, Sqoop, Kafka, AWS , Azure, GCP PaaS components, CDH Technical/Functional Skills -MUST HAVE SKILLS
- Strong hands on experience in Python programming machine learning and data engineering packages like pandas, numpy, scikit, keras, tensorflow, etc.
- Experience in operations in a production system, for a system heavily involving ML workloads
- Proficiency with various techniques in ML such as Regression, Classification, Forecasting and Cluster Analysis
- Strong understanding of modern machine learning methods and deep learning architectures and paradigms, e.g., Inception, ResNet/ResNext etc. Can train Computer Vision models on a GPU or multiple GPUs.
- Strong understanding across Cloud and infrastructure components (server, storage, network, data, and applications) to deliver end to end Cloud Infrastructure architectures and designs.
- Good understanding of data structures, data modeling and software architecture.
- Deep knowledge of math, probability, statistics and algorithms
- Exposure to Kubernetes, Docker, and/or cloud deployment technologies
- Demonstrable experience in architecting large scale cloud migration projects
- Knowledge of further Cloud technologies (AWS/Azure/GCP PaaS, Talend/Informatica/Snowflake)
- Deep understanding of database and analytical technologies in the industry including MPP and NoSQL databases, Data Warehouse design, BI reporting and Dashboard development.
- Experience with tools such as Spark, Hive, Sqoop, Kafka, Oozie, Hue, Zookeeper, HCatalog, Solr, etc.
- Proficient understanding of Underlying infrastructure for Big Data Solutions (Clustered/Distributed Computing, Storage, Data Center Networking)
- Experience in deployment of a large distributed Big Data Application.
- Drive the system design decisions of ML/DL based solutions, for both cloud and on-premise environments.
- Designing and implementing data engineering pipelines that serve curated datasets to business intelligence and reporting.
- Natural Language Processing for entity, topic clusters and relationship extraction
- Delivery of customer Cloud Strategies, aligned with customers business objectives and with a focus on Cloud Migrations
- Solution Design experience on Data Lake, Data Warehouse and Analytics systems
- Review and analyze relevant documentation to ensure the understanding of an application/offering's function and capabilities. Conduct relevant research to increase understanding in support of developing comprehensive solutions.
- Facilitates and/or participates in key Agile rituals including sprint planning, daily scrum meetings, sprint reviews, and sprint retrospectives across Scrum teams.
- Translate user stories and business requirements to technical solutions by building quick prototypes or proof of concepts with several business and technical stakeholder groups in both internal and external organizations.
- Develop tools and libraries that will enable rapid and scalable development in the future