Data Analyst

Introduction
At IBM, work is more than a job – it’s a calling: To build. To design. To code. To consult. To think along with clients and sell. To make markets. To invent. To collaborate. Not just to do something better, but to attempt things you’ve never thought possible. Are you ready to lead in this new era of technology and solve some of the world’s most challenging problems? If so, lets talk.

Your Role and Responsibilities

Our team enables the application of data for improving the efficiency, reliability and effectiveness of IBM Cloud and the development of platforms and applications for the same. Our focus spans the gamut of IBM cloud infrastructure operations across compute, networking and storage and involves active collaboration with the broader operations, SRE and development teams.

As a data analyst you will have the opportunity to transform diverse sources of operational data into valuable metrics, information and insight for understanding and improving the reliability, availability, and efficiency of our operations. You will have the responsibilities for analyzing the data, identifying the implications and implementing data-driven optimization strategies. You will part of a team realizing the data-driven vision for Cloud infrastructure operations and optimization running the gamut from regular/continuous data analysis for understanding status of operations, issue identification, root-cause analysis, mitigation and capacity management solutions.

Applicants with experience in the areas of developing and deploying machine learning techniques for practical applications, cloud and data center infrastructure operations, cloud native applications/services development and deployment would be preferred

Required Technical and Professional Expertise

• Bachelor’s degree in computer science/engg. or related field.
• At least 2 years of experience working on data integration, data integrity, data analytics or data science projects. (industry or experience in post-bachelor degree programs can count towards this criteria, as appropriate)
• Hands-on experience with production database and data warehousing systems – SQL, and/or cloud-native ones like Elasticsearch..
• Experience demonstrating desired qualities like attention to details, self-directedness, good problem-solving and multi-tasking skills.
• Programming experience for data analysis.

Preferred Technical and Professional Expertise

• Masters or equivalent degree in statistics/machine learning/AI/allied fields.
• Knowledge and application of statistical analysis techniques; machine learning techniques like regression, classification, clustering, reinforcement learning; and/or AI techniques like natural language processing and deep learning.
• Experience with technologies enabling reliable data processing pipelines such as Kafka, Elasticsearch, Splunk; database and data visualization technologies for operations such as SQL dbs, Influxdb, Grafana, Kibana.
• Programming experience in Python or Java.