Securities Services Technology - Data Scientist

Role Overview: At Arctic Wolf, as a Data Scientist in the Artificial Intelligence Security Operations Team, you will play a vital role in developing intelligent systems to detect threats, identify anomalies, and enhance the automation and efficiency of security operations. You will work at the intersection of data science, artificial intelligence, and security operations to design machine learning models and data-driven systems that analyze large-scale security telemetry. Key Responsibilities: - Build and deploy machine learning models for threat detection, anomaly detection, and behavioral analytics within security datasets. - Develop Python-based data pipelines and processing workflows to analyze large volumes of security telemetry and operational data. - Collaborate with engineering and platform teams to integrate models into production systems and security automation platforms. - Apply statistical modeling and machine learning techniques to identify unusual patterns, emerging risks, and threats across complex data sources. - Perform feature engineering and dataset design to enhance model performance and detection accuracy. - Continuously evaluate model performance through experimentation, validation, and iterative improvements. Qualifications Required: - 4+ years of experience in Data Science, Machine Learning, or Applied Artificial Intelligence roles. - Strong Python programming skills with experience in writing high-quality, production-ready code. - Experience with machine learning frameworks such as Scikit-learn, PyTorch, TensorFlow, or Extreme Gradient Boosting. - Hands-on experience working with large datasets, feature engineering, and data preprocessing pipelines. - Experience building models for anomaly detection, classification, clustering, or behavioral analysis. - Proficiency in using Structured Query Language and data analysis tools for manipulating large datasets. - Strong analytical thinking and the ability to translate complex data into actionable insights. - Experience in security, fraud detection, or risk analytics datasets. - Familiarity with cloud-based data platforms, distributed data processing frameworks, or machine learning deployment environments. - Experience in security operations, detection engineering, or large-scale monitoring environments. Additional Company Details: Arctic Wolf is a high-growth company recognized by Forbes, CNBC, Fortune, CRN, Gartner Peer Insights, and International Data Corporation MarketScape. The company is dedicated to bold growth and shaping the future of security operations while fostering a collaborative and inclusive work environment. Arctic Wolf values diversity and inclusion, corporate responsibility, and offers compelling compensation and benefits packages to its employees. Please note that as a candidate interviewing remotely, you are expected to be on camera during all video interviews to foster authentic connection and engagement. If you encounter any challenges with video use, kindly notify Arctic Wolf in advance for appropriate accommodations. Arctic Wolf is an Equal Opportunity Employer committed to providing a welcoming, accessible, respectful, and inclusive environment for all employees. Accommodations are provided for candidates and employees with disabilities or specific needs where possible. Role Overview: At Arctic Wolf, as a Data Scientist in the Artificial Intelligence Security Operations Team, you will play a vital role in developing intelligent systems to detect threats, identify anomalies, and enhance the automation and efficiency of security operations. You will work at the intersection of data science, artificial intelligence, and security operations to design machine learning models and data-driven systems that analyze large-scale security telemetry. Key Responsibilities: - Build and deploy machine learning models for threat detection, anomaly detection, and behavioral analytics within security datasets. - Develop Python-based data pipelines and processing workflows to analyze large volumes of security telemetry and operational data. - Collaborate with engineering and platform teams to integrate models into production systems and security automation platforms. - Apply statistical modeling and machine learning techniques to identify unusual patterns, emerging risks, and threats across complex data sources. - Perform feature engineering and dataset design to enhance model performance and detection accuracy. - Continuously evaluate model performance through experimentation, validation, and iterative improvements. Qualifications Required: - 4+ years of experience in Data Science, Machine Learning, or Applied Artificial Intelligence roles. - Strong Python programming skills with experience in writing high-quality, production-ready code. - Experience with machine learning frameworks such as Scikit-learn, PyTorch, TensorFlow, or Extreme Gradient Boosting. - Hands-on experience working with large datasets, feature engineering,