State Street
Hyderābād
Investment Banking & Asset Management
Who we are looking for
The AI & Data Engineer – Associate Vice President, will work as one of the GCS AI (Global Cyber Security Artificial Intelligence) Agile team members by applying various AI technologies (ML/DL/RPA/NLP/NLU/GAN etc.), through the phases of cybersecurity/business problems discovering, solutions, architecture design, data wrangling, PoC, implementation and support deployment of the resulting AI services while focusing on scientific implementation and validation of quantitative cybersecurity and financial models.
Who We Are:
State Street’s GCS Artificial Intelligence is a strategic global Agile team, which is formed under Architecture and Engineering management of GCS Leadership. It has the mission to explore, enable and exploit artificial intelligence, machine learning, deep learning, natural language processing, computer vision and cognitive computing at scale for countless use cases across cybersecurity’s specific domains of cyber threat intelligence, security operation, access control, network security, security vulnerability, insider threat, data loss protection, etc.
GCS AI team has a mixed of intelligence technologies including, mathematic modeling, data science, security engineering, and software engineering capabilities. This team engages with GCS business lines to explore, prototype, solution use cases, implementation, and delivery true business value. What you will be responsible for
Responsible for overall delivery of assigned project and/or product, solution & architecture design, model development and validation, IT implementation and Quality Assurance. • Become a subject matter expert of cybersecurity in ground-level model and algorithm design, development, and validation by converting all kinds of security data and models to mathematical and computer science level design and implementation with consideration of space and time complexity. • Integrate, customize, and train well known models and algorithms in open source libraries to solve global cybersecurity, financial markets problems and perform validation and bug fixes. • Build models and algorithms from scratch time to time and perform validation including but not limited to goal function, loss function, accuracy function, error function, similarity function, optimization function, and simulation function depending on type of problem and techniques used. • Write model specification and create AI various tasks & models about problem statement, assumption, data input, methodology, implementation framework, and test result. • Support IT integration, QA/UAT and deployment of Cognitive micro services, operationalizing and productizing resulting models and cognitive solutions. • Support production issue pertinent to model and algorithm including the ones used in open source libraries if any.
Education & Preferred Qualifications
Bachelor degree required (major in computer science, mathematical finance, data science, and financial engineering); Master/PhD from top ranked university preferred.
8+ years of hands on experience with classical AI/ML algorithms and familiar with deep learning neural network like various CNN, RNN and GAN based models and comfortable with natural language understanding and processing and computer vision algorithms.
8+ years of solid modern, object-oriented or functional programming and design experience (Python, R, Java, C++, SQL) • Solid mathematics capabilities including but not limited to linear algebra, calculus, statistics, probability theory, stochastic calculus, differential equations, matrix manipulation, etc. • Experience with at least one Data Science, Machine Learning Frameworks and AI Platforms, like TensorFlow, PyTorch, Scikit-learn, DataRobot, Amazon AI services, Google Cloud AI, Microsoft Azure AI, etc.
Experience with Setting up machine learning problems using Time Series, Anomaly Detection, Natural Language Understanding & Processing etc. Evaluating performance and efficacy of Machine Learning problems. • Familiar with major cybersecurity domains, including but not limited to cyber engineering, cyber threat intelligence, security operation, access control, network security, security vulnerability, insider threat, data loss protection, etc. • Excellent written and verbal communication skills at all stakeholder levels across multiple countries. • Open minded, fast learner, self-motivated, result driven, detail oriented, candid attitude, team player.
Experience in any of the following is highly desirable: • Prior data scientist role in cybersecurity and/or financial institution and model validation experience • Data Science and Machine Learning Frameworks (DataRobot, Amazon CodeGuru/SageMaker, Amazon Lex/Fraud Detector/Augmented AI, TensorFlow, PyTorch, Scikit-learn, Apache Spark / MLlib etc.) • Linux / Bash scripting, structured and unstructured data management tools (Snowflake, Graph DB, PostgreSQL, Hadoop, etc.) • Continuous integration & continuous deployment environments, DevOps pipelines tools and skills (Azure, AWS, GIT, Maven, Jenkins, Docker, Kubernetes, etc.)
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