ETRM - Insider Threat & Data Scientist - Officer

Company:
Location: Hyderabad, Telangana

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Enterprise Technology Risk Management, Insider Threat & Data Scientist, Officer

It is an exciting time to join State Street Corporation (SSC) in the Enterprise Risk Management (ERM) organization as member of the Enterprise Technology Risk Management (ETRM) team. State Street is the industry leader in investment management, research & trading and servicing. ETRM is responsible for oversight, monitoring, and advisement around the management of IT risks across the State Street enterprise.

The Second Line of Defense ETRM Team is seeking a candidate to design, develop and deliver various data science-based insights and create proof of concepts in the area of Cyber, Information Technology, Operational and Resiliency risks. Also apply the data analytics to assess insider threat monitoring and detection capabilities. The candidate will closely work with teams across multiple Risk, Control and Technology divisions and report into a senior Enterprise Technology Risk Manager. The position is based out of Hyderabad, India.

General Roles and Responsibilities

The candidate will be expected to work with a diverse set of data sources such as vulnerability data, SIEM logs, CMDB, Incident, BCMS, Technology Issues, Vendor Engagement & Issues, HR, Fraud, Bribery and Employee relation issues data, semi-structured and unstructured data to build statistical / machine learning models. The candidate will assess the effectiveness and accuracy of new data sources and data gathering techniques. Must be able to compile information and prepare reports based on both manual and automated sources. Also assist in the evaluation, research and development of data models. Below are some of the roles and responsibilities:

  • Identify relevant data sources and sets to mine for business needs
  • Enhance data collection procedures to include information that is relevant for building analytic systems. Automate the data collection process to the extent possible
  • Establish techniques for preprocessing of structured and unstructured data
  • Devise and utilize algorithms and models to mine big data stores, perform data and error analysis to improve models and clean and validate data for uniformity and accuracy
  • Process complex data sets using advanced querying, visualization and analytics tools
  • Analyze large amounts of raw information to find trends / patterns to extract valuable business insights
  • Interpret patterns and trends to be used to analyze and report insider threat activities
  • Process large volumes of data to identify user behavior that may be detrimental to State Street
  • Provide quality assurance on the insider threat use cases implemented
  • Build predictive / forecasting models and machine learning algorithms
  • Present information using data visualization techniques
  • Establish and maintain relationships with respective risk management and technical teams
  • Contribute to the continued development of risk excellence culture within State Street

Qualification:

The ideal candidate must possess the following:

  • Graduate in Computer Engineering (preferably BTECH / BCA / MCA)
  • Minimum 6 – 10 years of overall experience with demonstrated track record in data science solutioning
  • Good understanding of supervised learning, unsupervised learning and deep learning frameworks
  • Excellent understanding of machine learning techniques and algorithms such as k-NN, Naive Bayes, SVM, Decision Forests etc.
  • Experience with common data science toolkits such as R, Weka, NumPy, MatLab, SAS, Python etc. to manipulate data and draw insights from large data sets
  • Experience in building scalable and efficient tools to process large volumes of data to identify user behaviour
  • Experience of applying data science methods to real-world data problems
  • Experience in utilizing visualization tools such as Tableau, Power BI etc. to take advantage of the growing volume of information
  • Critical thinking and problem-solving skills are essential
  • Familiarity in Information Security Frameworks including the ISO 27000 family and NIST is desirable
  • Exceptional communication and analytical skills
  • Proficient in Microsoft Access, Excel, and working knowledge in SharePoint
  • Ability to multitask and navigate competing priorities

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