Data Scientist jobs at Intercontinental Exchange - Ice in United States, Atlanta

About Our Technology Stack

You'll be working with a modern, on-premises data stack that includes:

• Apache Airflow for workflow orchestration (self-hosted on Kubernetes)
• dbt for data transformation and testing
• Apache Flink for stream processing and real-time data workflows
• Kubernetes for containerized deployment and scaling
• Git-based version control and CI/CD for data pipelines
• Oracle Exadata for data warehousing
• Kafka for messaging and event streaming

We emphasize building systems that are maintainable, scalable, and focused on enabling self-service data access while maintaining high standards for data quality and governance.

Responsibilities

• Design, build, and maintain our on-premises data orchestration platform using Apache Airflow, dbt, and Apache Flink
• Create self-service capabilities that empower teams across the organization to build and deploy data pipelines without extensive engineering support
• Implement robust data quality testing frameworks that ensure data integrity throughout the entire data lifecycle
• Establish data engineering best practices, including version control, CI/CD for data pipelines, and automated testing
• Collaborate with ML/AI teams to build scalable feature engineering pipelines that support both batch and real-time data processing
• Develop reusable patterns for common data integration scenarios that can be leveraged across the organization
• Work closely with infrastructure teams to optimize our Kubernetes-based data platform for performance and reliability
• Mentor junior engineers and advocate for engineering excellence in data practices

Knowledge and Experience

• 5+ years of professional experience in data engineering, with at least 2 years working on enterprise-scale data platforms
• Deep expertise with Apache Airflow, including DAG design, performance optimization, and operational management
• Strong understanding of dbt for data transformation, including experience with testing frameworks and deployment strategies
• Experience with stream processing frameworks like Apache Flink or similar technologies
• Proficiency with SQL and Python for data transformation and pipeline development
• Familiarity with Kubernetes for containerized application deployment
• Experience implementing data quality frameworks and automated testing for data pipelines
• Knowledge of Git-based workflows and CI/CD pipelines for data applications
• Ability to work cross-functionally with data scientists, ML engineers, and business stakeholders

Preferred Knowledge and Experience

• Experience with self-hosted data orchestration platforms (rather than managed services)
• Background in implementing data contracts or schema governance
• Knowledge of ML/AI data pipeline requirements and feature engineering
• Experience with real-time data processing and streaming architectures
• Familiarity with data modeling and warehouse design principles
• Prior experience in a technical leadership role

Responsibilities

• Develop and execute technical strategies for API, File, and data share platforms
• Own the creation of cross platform standards documentation, success measurements and tools and implementation roadmaps
• Collaborate with sales and stakeholders to identify opportunities and build business cases
• Analyze market trends and client feedback to enhance products and drive innovation
• Design user experiences that align with business goals and ensure scalability
• Prioritize projects and manage resources efficiently across development, QA, and operations
• Develop and champion process improvements and workflow automation initiatives.
• Drive information gathering, scoping, planning, and training sessions with stakeholders

Technical Skills

• Intermediate level experience in Java, .NET, HTML, Javascript or other Front End Application Development Framework . We are not looking for a developer, but someone who can understand the flow of code, and is able to build demonstrations and prototypes
• A solid understanding of zero footprint, web technologies and communication protocols
• Strong knowledge of Python for scripting, data analysis, and data manipulation

Business Acumen

• Strong understanding of market data systems, governance, and entitlements
• Excellent stakeholder management and communication skills
• Knowledge and awareness of Market Trends

Soft Skills

• Excellent communication, problem-solving and analytical skills
• Familiarity with project management methodologies and process management in dynamic environments
• Comfortable in a fast-paced and dynamic environment

Experience:

• 5+ years of experience working in roles that combine technology implementation, planning, and transformation

Education and Technical Knowledge:

• Understanding of data storage, data modeling, data structures, and common query languages
• Bachelor's degree or equivalent preferred

Job Purpose

The Data Scientist will join the Quant Group which designs, implements, and supports enterprise quantitative models and systems. The primary role of this position will be to support the design and development of financial data models and provide data support for the Quant and Risk divisions. The role will use a variety of data science, analytics and engineering tools and techniques to solve diverse, data focused problems across the business. The candidate for this job must have the ability to work in a fast-paced environment, formulate and articulate solutions, defend assumptions and be highly detail oriented. This role requires frequent interaction with Quant Research, Risk Managers, Developers and Senior Management.

Responsibilities

• Perform data exploration and statistical analysis for quantitative research purposes
• Data preparation, validation, and visualization of various data sets such as time series of financial derivatives
• Build production quality, data driven software solutions to support data management and analysis
• Develop ETL applications to support core quant and risk team data requirements
• Diagnose and profile data issues and recommend ways to improve data reliability, efficiency, and quality
• Coordinate with quantitative research and business experts to develop and refine data management best practices, policies, and procedures
• Provide documentations and/or presentations to illustrate methods, techniques, and findings for individuals with diverse professional backgrounds
• Manage large data sets and interpret diverse database architecture across various platforms such as Oracle, Postgres, Snowflake, etc.
• Serve as a liaison between technology, operations, product management and the Financial Engineering teams
• Engage in innovative research tasks in the quantitative finance and data science field

Knowledge and Experience

• Bachelor’s degree in Data Science/Analytics, Engineering, Mathematics, Statistics or similar required; Post Graduate degree in Data Science, Engineering, Mathematics, Statistics or similar preferred
• Statistical programming experience in Python, R, MATLAB, C/C++ or Java
• Working knowledge of SQL and experience working with relational databases
• Ability to work in a high-performance, high-velocity environment
• Strong analytical and organizational skills with acute attention to detail
• Strong communication skills
• Customer focused and results oriented
• Advanced Statistics knowledge related to Time Series preferred
• Experience with code versioning tools such as Git preferred
• Experience in Quantitative Finance and/or Financial Derivatives preferred

Responsibilities

• Conduct integrated operational and compliance related testing of manual and automated controls.
• Develop a thorough understanding of the ICE’s North American derivatives exchange and clearinghouse operations.
• Assist with the completion of audit risk assessments.
• Complete audit assignments within established time frames and budgets.
• Perform independent appraisal of policies and procedures.
• Document audit procedures performed in accordance with departmental procedures and standards.
• Communicate identified control deficiencies to management effectively.
• Maintain effective relationships with internal stakeholders.
• Draft audit reports and participate in exit meetings with management to discuss findings and responses.
• Travel to other locations as required for internal audit and training purposes.

Knowledge and Experience

• Minimum of Bachelor's degree or with a commitment to maintaining or obtaining appropriate professional certification (e.g. CIA, CPA, CFA, CFE, CISA).
• 2+ years in internal audit or equivalent experience.
• Excellent communication, organization and time management skills with appropriate attention to detail.
• Ability to perform multiple projects simultaneously.
• Must be proficient in Word, Excel, and PowerPoint.
• Ability to adapt in a high growth, rapidly evolving industry.
• Participate in audits of the general business and information technology functions in supporting the execution of the annual audit plan.
• Knowledge of financial services industry and infrastructure a plus.
• Ability to travel up to 10 percent; including international.

Job Purpose

The Sr. Data Quality Assurance Analyst will be responsible for developing, maintaining, and automating tests to ensure all data feeds and compliance reports are accurate and complete. This role requires frequent interaction with software developers, testers, product managers, compliance and market supervision professionals to ensure delivery of data quality and reports to internal and external users for business decision-making and government compliance needs. Additionally, the role will involve data analysis and automation using Python coding to enhance the efficiency and accuracy of compliance reporting.

Responsibilities

• Strong background in functional testing with the ability to design and develop test strategy and test cases.
• Gather information from disparate systems to aid problem resolution.
• Work with Business Analysts, Java and SQL Development engineers to review technical requirements and produce test strategies, test scenarios, and test cases to validate the correctness of data in applications and reports
• Testing skills to validate the transformation logic; diagnostic and debugging skills. Performing various data reconciliations
• Responsible for writing, executing, and debugging SQL queries to perform data completeness, correctness, data transformation, and data quality testing.
• Ensure content and structure of all testing documents/artifacts are documented and maintained.
• Perform all aspects of verification, including functional, structural, regression, and system testing.
• Experience participating in all aspects of a full-lifecycle development methodology, and related quality concepts and processes.
• Excellent attention to detail.
• Ability to work in an agile environment with an iterative approach to development.
• Conduct data analysis to identify trends, patterns, and insights that can improve compliance reporting.
• Develop and maintain automation scripts using Python to streamline testing and reporting processes.

Knowledge and Experience

• Requires experience/knowledge of the following functional areas:
• 5+ years of experience in software testing, with 3 years of experience in enterprise data warehouse environments.
• Proficient in SQL and database systems.
• Experience with Shell Scripting and Unix.
• Experience testing data for data marts, data warehouses, and data integration solutions.
• Track record of completing assignments on time with a high degree of quality.
• Excellent analytical, problem-solving, communication, and interpersonal skills.
• Ability to set priorities and multi-task in a fast-paced environment.
• Extensive knowledge of testing process, testing methodology analysis, and defect reporting tools.
• Ability to work independently and productively under pressure.
• Strong organizational skills and decision-making ability.
• Bachelor’s Degree or equivalent.
• Proficiency in Python coding for automation and data analysis.

Job Purpose

The Data Scientist will join the Quant Group which designs, implements, and supports enterprise quantitative models and systems. The primary role of this position will be to support the design and development of financial data models and provide data support for the Quant and Risk divisions. The role will use a variety of data science, analytics and engineering tools and techniques to solve diverse, data focused problems across the business. The candidate for this job must have the ability to work in a fast-paced environment, formulate and articulate solutions, defend assumptions and be highly detail oriented. This role requires frequent interaction with Quant Research, Risk Managers, Developers and Senior Management.

Responsibilities

• Perform data exploration and statistical analysis for quantitative research purposes
• Data preparation, validation, and visualization of various data sets such as time series of financial derivatives
• Build production quality, data driven software solutions to support data management and analysis
• Develop ETL applications to support core quant and risk team data requirements
• Diagnose and profile data issues and recommend ways to improve data reliability, efficiency, and quality
• Coordinate with quantitative research and business experts to develop and refine data management best practices, policies, and procedures
• Provide documentations and/or presentations to illustrate methods, techniques, and findings for individuals with diverse professional backgrounds
• Manage large data sets and interpret diverse database architecture across various platforms such as Oracle, Postgres, Snowflake, etc.
• Serve as a liaison between technology, operations, product management and the Financial Engineering teams
• Engage in innovative research tasks in the quantitative finance and data science field

Knowledge and Experience

• Bachelor’s degree in Data Science/Analytics, Engineering, Mathematics, Statistics or similar required; Post Graduate degree in Data Science, Engineering, Mathematics, Statistics or similar preferred
• Statistical programming experience in Python, R, MATLAB, C/C++ or Java
• Working knowledge of SQL and experience working with relational databases
• Ability to work in a high-performance, high-velocity environment
• Strong analytical and organizational skills with acute attention to detail
• Strong communication skills
• Customer focused and results oriented
• Advanced Statistics knowledge related to Time Series preferred
• Experience with code versioning tools such as Git preferred
• Experience in Quantitative Finance and/or Financial Derivatives preferred

Responsibilities

• Develop and implement advanced analytics models using machine learning and AI techniques.
• Collaborate with cross-functional teams to understand business needs and provide data-driven solutions.
• Design and maintain scalable and robust data pipelines in Snowflake.
• Analyzing data and sharing meaningful insights
• Write clean, efficient, and well-documented Python code to perform data analysis and modeling.
• Stay up to date with the latest technologies and trends in data science and machine learning.

Knowledge and Experience

• Bachelor’s or Master's in Computer Science, Analytics, Statistics, Mathematics, or a related field.
• Minimum of 3 years of experience in a data science role, with a focus on Snowflake, Python, SQL, Machine Learning, and AI.
• Minimum of 3 years of experience in Tableau or any other data visualization tool
• Proven track record of developing and deploying machine learning models in a production environment.
• Strong analytical and problem-solving skills.
• Excellent communication and collaboration abilities.

Preferred

• Experience with cloud platforms and services.
• Knowledge of additional programming languages and frameworks is a plus.