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The Data Scientist is responsible for developing and implementing AI-driven solutions to enhance cybersecurity measures within the organization. This role involves leveraging data science techniques to analyze security data, detect threats, and automate security processes. The Data Scientist will work closely with cybersecurity teams to identify data-driven automation opportunities, strengthening the organization’s security posture.
Job Responsibility:
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
Requirements:
Master’s degree and 1 to 3 years of experience with one or more analytic software tools or languages (e.g., SAS, SPSS, R, Python)
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)
Diploma and 7 to 9 years of experience with one or more analytic software tools or languages (e.g., SAS, SPSS, R, Python)
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
Nice to have:
Experience with one or more analytic software tools or languages (e.g., SAS, SPSS, R, Python)
Demonstrated skill in the use of applied analytics, descriptive statistics, feature extraction and predictive analytics on industrial datasets
Strong foundation in machine learning algorithms and techniques
Experience in statistical techniques and hypothesis testing, experience with regression analysis, clustering and classification
Any AWS Developer certification (preferred)
Any Python and ML certification (preferred)
Any SAFe Agile certification (preferred)
Initiative to explore alternate technology and approaches to solving problems
Skilled in breaking down problems, documenting problem statements, and estimating efforts
Excellent analytical and troubleshooting skills
Strong verbal and written communication skills
Ability to work effectively with global, virtual teams
High degree of initiative and self-motivation
Ability to manage multiple priorities successfully
Team-oriented, with a focus on achieving team goals