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Palo Alto Sr Staff Engineer Software Threat Data Platform United States, California
End-to-end backend development of features and core components across their entire life cycle (design, develop, test, deploy, maintain). Design, develop, maintain and optimize data pipelines to extract, transform, and load...
Drive business value through data science and advanced analytics. Conduct exploratory data analysis to understand the strengths and limitations of complex data sets and identify the appropriate analytical approach. Design...
BS and a minimum of 3 years of relevant industry experience is required. Proficient developer with 3+ years proven programming skills using Python, Pandas, Matplotlib and other key related tools....
Bachelor's Degree. 5+ years of relevant work experience managing cloud infrastructure. Strong background in managing cloud infrastructure resources (CPUs / GPUs) showing aptitude for understanding complex financial structures and translating...
Typically requires a minimum of 8+ years of experience in data analysis, data quality or similar role, driving large scale complex business process/technology transformation initiatives and handling large-scale data systems....
Master’s degree or foreign equivalent in Math, Statistic, Mechanical Engineering, Computer Science or related field and 2 years of experience in the job offered or related occupation. 2 years of...
Experienced in managing and troubleshooting MacOS and Linux systems using scripting languages such as Bash, PowerShell, Python or other. Experience diagnosing and resolving hardware & software issues. Experience writing technical...
End-to-end backend development of features and core components across their entire life cycle (design, develop, test, deploy, maintain). Design, develop, maintain and optimize data pipelines to extract, transform, and load...
Data Scientists are responsible for analyzing and interpreting large and complex datasets to uncover insights that inform business decisions and drive innovation. They use a combination of statistical and machine learning techniques, as well as programming languages such as Python and R, to extract, clean, and transform data. They also use tools such as SQL, Hadoop and Spark to work with large datasets and perform data analysis.
Data Scientists work closely with cross-functional teams, such as product managers, marketing and operations, to understand their specific data needs and provide them with insights to make informed decisions. They also collaborate with data engineers to build and maintain the infrastructure necessary for data analysis. They also use data visualization tools such as Tableau and Power BI to create interactive dashboards and reports to communicate data insights clearly and effectively to non-technical stakeholders.