Analyst, Index Operations at Intercontinental Exchange Holdings, Inc.

Hyderabad, Telangana, India -

Full Time

Start Date

Immediate

Expiry Date

03 Sep, 26

Salary

0.0

Posted On

05 Jun, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, SQL, Generative AI, Machine Learning, ETL Pipelines, Pandas, Data Visualization, Power BI, Streamlit, Statistical Modeling, Outlier Detection, Web Scraping, Microsoft Excel, Data Normalization, Time-series Analysis, Clustering

Industry

Financial Services

Description

Job Description Job Purpose Intercontinental Exchange (NYSE: ICE) is a Fortune 500 company that designs, builds and operates digital networks to connect people to opportunity. We provide financial technology and data services across major asset classes that offer our customers access to mission-critical workflow tools that increase transparency and operational efficiencies. We operate exchanges, including the New York Stock Exchange, and clearing houses that help people invest, raise capital and manage risk across multiple asset classes. Our comprehensive fixed income data services and execution capabilities provide information, analytics and platforms that help our customers capitalize on opportunities and operate more efficiently. At ICE Mortgage Technology, we are transforming and digitizing the U.S. residential mortgage process, from consumer engagement through loan registration. Together, we transform, streamline and automate industries to connect our customers to opportunity. We are seeking an Analyst, Index Operations with a primary focus on Python development, leveraging Generative AI (Gen AI) and advanced Machine Learning methodologies to automate and enhance the quality of input data for our index franchise. You will be responsible for designing, implementing, and maintaining advanced algorithms and data pipelines that power thematic and benchmark indices, while ensuring alignment with both internal and regulatory standards. Responsibilities Design and implement Python-based algorithms for systematic index rebalancing in compliance with specific index rulebooks. Incorporate logic to identify and explain constituent additions, deletions, and weight changes. Develop statistical models to impute missing values in historical datasets using real-world proxies and techniques. Detect and resolve high-variance anomalies using outlier detection, clustering, and time-series analysis. Identifying, extracting, and transforming unstructured data into structured data for further processing, build validation frameworks to compare raw vs. cleansed data and measure data quality improvements. Extract and normalize data from multiple sources including flat files, APIs, web scraping, and databases eg: SQL. Create scalable ETL pipelines using tools like Pandas etc. where applicable. Evaluate and implement LLM-based solutions to automate repetitive tasks such as document summarization or classification etc. Work closely with index analysts, product teams, and compliance to ensure automation aligns with regulatory and business logic. Present findings, models, and data products through dashboards (e.g., Power BI, Streamlit) and technical documentation. Own the development, optimization, and maintenance of scalable data pipelines using Python and cloud-based solutions to support index data flows for thematic and benchmark indices. Drive continuous improvements in data quality, algorithmic performance, and system reliability through regular code refactoring, Converting legacy codes, model updates, and data validation routines. Knowledge and Experience Undergraduate degree, preferably in Math or Technology. 3+ years of relevant work experience. Strong coding and working knowledge with Python, Structured Query Language and Microsoft Excel. Good data visualization skills in Python. Working experience in Generative AI and Machine Learning methodologies. Ability to work under stringent time constraints, multi-task and prioritize workload. Strong written and verbal communication skills are essential. Good organizational skills with keen attention to detail. Ability to work as a part of a team and independently. Preferred Knowledge and Experience Passed some or all three levels of the CFA Program or working towards the CFA charter. Knowledge of and/or experience within Equity and Fixed Income Markets, focus on data quality, identifying & analyzing corporate actions.

Responsibilities

Design and implement Python-based algorithms and scalable data pipelines to automate index rebalancing and enhance data quality for thematic and benchmark indices. Leverage Generative AI and Machine Learning to transform unstructured data and automate repetitive tasks like document classification.