Cyber Security Data Science Analyst

Key Skills

Python Programming, Database, R Programming, Splunk, SAS, ETL frameworks

Job Description

As part of the Cyber Security Data Intelligence and Innovation (CDI2) team at Truist, you will work to understand business goals, operations and objectives and use your data science knowledge and experience to identify, explore, and validate new use cases; build rapid prototypes and run pilots; test key technical and business assumptions in collaboration with key stakeholders; develop and utilize project plans with clear stage gates; and implement and scale up solutions that meet all stage gate criteria. You will collaborate with other data scientists as well as other data engineers, software developers, and visualization experts who are part of the CDI2 team and who manage the cyber security data warehouse (data pipeline design, development, operations and maintenance), build and update key metrics used for cyber security operations and for executive reporting, and create data visualizations for rapid self-service consumption of key metrics used by the Cyber Security Division and other internal partners.

In this role you will be responsible for the following types of tasks: Responsible for gathering, analyzing, documenting and maintaining all security data requirements related to the business applications, interfaces and reporting environments. Apply standards and best practices to ensure enterprise data is protected, accurate, complete, current, understandable and accessible. Work closely with internal clients, business analysts and development project teams to resolve information flow and content issues.

ESSENTIAL DUTIES AND RESPONSIBILITIES

Following is a summary of the essential functions for this job. Other duties may be performed, both major and minor, which are not mentioned below. Specific activities may change from time to time.

• Identify and explore potential data science use cases, including business value (eg, cost savings, risk reduction or other value), data science methodologies, and key implementation assumptions/barriers.
• Identify, gather, and analyze data for data science use cases, using a wide variety of methods to identify key variables of interest.
• Develop conceptual proof of concepts for using data science methods to add value and pitch.
• Build prototype models and pilot test from a technical perspective and solicit feedback from key stakeholders and iterate the model.
• At key stage gate points, consider if a specific project should be stopped, paused, put on a roadmap based on new information—eg, the projected value is lower than originally thought, the cost to build and/or maintain.
• Gather, review, analyze, profile, validate and map system data into the cyber security data warehouse to meet cyber security reporting and operational analytical needs.
• Perform data analytics and troubleshooting on security data ingestion issues reported by production support and other teams.
• Develop solutions and recommendations for improving data integrity issues. Analyze data issues and work with development teams for problem resolutions. Identify problematic areas and conduct research to determine the best course of action to correct the data, identify, analyze and interpret trends and patterns in complex datasets.
• Work with extract, transform and load (ETL) developers to test and validate data attributes and with other business analysts to ensure data is integrated consistently, regardless of the source system.
• Take ownership of issues through resolution, including close coordination between business representatives, IT staff, and data warehouse administrators.
• Assist in documenting the company's existing solution architecture and technology portfolio; make recommendations for improvements and/or alternatives
• Work with source system business analysts to understand system and log nuances and resolve data issues.

QUALIFICATIONS

Required Qualifications:

The requirements listed below are representative of the knowledge, skill and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

• Bachelor’s degree in Information Technology, Information Systems, Computer Science, Economics, Data Analytics or another Business-related field, or equivalent education and related training
• Experience in data analytics, statistical analytics, data transformation, data reconciliation and/or sophisticated data presentation

Thorough understanding of data science and manipulation techniques.

• Proficient in at least one programming language such as Python or R.
• Familiarity with the different components of an Information Security Program and understanding of how to successfully correlate disparate logs and cyber related data to accurately identify trends, behavior baselines, and outliers that represent possible risks
• Understanding of Enterprise Data Warehouse concepts and prior experience applying that understanding to query data in a Very Large Database (VLDB) environment

Preferred Qualifications:

• Previous experience with cyber security intelligence and security analytical packages (eg, Securonix)
• Previous experience with Splunk
• Banking or financial services experience
• Working knowledge of SAS, Anaconda and other analytic tools
• Ability to recommend the growth, addition, and retirement of data analytics toolsets
• Other Job Requirements / Working Conditions
• Sitting: Constantly (More than 50% of the time)
• Visual / Audio / Speaking: Able to access and interpret client information received from the computer and able to hear and speak with individuals in person and on the phone.
• Manual Dexterity / Keyboarding: Able to work standard office equipment, including PC keyboard and mouse, copy/fax machines, and printers.
• Availability: Able to work all hours scheduled, including overtime as directed by manager/supervisor and required by business need.
• Travel: Minimal and up to 10%