#R-226785
ams to identify data-driven automation opportunities, strengthening the organization's security posture.
Roles & Responsibilities:
Develop analytics to address an organization's business or Engineering problems.
Collaborate with Data Engineers to translate Machine Learning algorithms into effective solutions.
Work in technical teams in development, deployment, and application of applied analytics, predictive analytics, and prescriptive analytics.
Perform exploratory and targeted data analyses using descriptive statistics and other methods to identify security patterns and anomalies.
Design and implement analytics pipelines leveraging MLOps practices.
Collaborate with data engineers on data quality assessment, data cleansing, and the development of operational data pipelines.
Contribute to data engineering efforts to refine data infrastructure and ensure scalable, efficient analytics.
Generate reports, annotated code, and other projects artifacts to document, archive, and communicate your work and outcomes.
Share and discuss findings with team members practicing SAFe Agile delivery model.
Must-Have Skills:
Master's / Bachelor's degree and 3 to 5 years of experience with one or more analytic software tools or languages (e.g., SAS, SPSS, R, Python) OR
Preferred qualifications:
Proficiency in Python and relevant ML libraries (e.g., TensorFlow, PyTorch, Scikit-learn)
Outstanding analytical and problem-solving skills; Ability to learn quickly; Excellent communication and interpersonal skills
Experience with data engineering and pipeline development
Experience in analyzing time-series data for forecasting and trend analysis
Experience with AWS, Azure, or Google Cloud
Experience with Databricks platform for data analytics and MLOps
Experience with Generative AI models (e.g., GPT, DALL• E, Stable Diffusion) and their applications in cybersecurity and data analysis
Experience working in Product team's environment
Experience working in an Agile environment
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