Infosys

Data Analyst

Job Description

Responsibilities: • Collect, clean, and organize large datasets from various sources • Perform data analysis using statistical methods, machine learning techniques, and data visualization tools • Identify patterns, trends, and anomalies within datasets to uncover insights • Develop and maintain data models to represent the organization's business operations • Create interactive dashboards and reports to communicate data findings to stakeholders • Document data analysis procedures and findings to ensure knowledge transfer Educational Requirements Master Of Science,Master Of Comp. Applications,Master Of Technology,Master Of Engineering,Bachelor Of Science,Bachelor Of Comp. Applications,Bachelor Of Technology,Bachelor of Engineering Additional Responsibities: • High analytical skills • A high degree of initiative and flexibility • High customer orientation • High quality awareness • Excellent verbal and written communication skills • Logical thinking and problem solving skills along with an ability to collaborate • Two or three industry domain knowledge • Understanding of the financial processes for various types of projects and the various pricing models available • Client Interfacing skills • Knowledge of SDLC and agile methodologies • Project and Team management Technical and Professional Requirements: • • 5+ years of experience as a Data Analyst or similar role. • Proven track record of collecting, cleaning, analyzing, and interpreting large datasets • Expertise in Pipeline designing and Validation • Expertise in statistical methods, machine learning techniques, and data mining techniques • Proficiency in SQL, Python, PySpark, Looker, Prometheus, Carbon, Clickhouse, Kafka, HDFS and ELK stack (Elasticsearch, Logstash, and Kibana) • Experience with data visualization tools such as Grafana and Looker • Ability to work independently and as part of a team • Problem-solving and analytical skills to extract meaningful insights from data • Strong business acumen to understand the implications of data findings


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