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Data Analyst, Third Party Indices 1532 views

The Third-Party Indices data team is responsible for onboarding, standardizing, validating, and publishing equity and fixed income indices, from worldwide benchmarks like the S&P 500 and NASDAQ to custom baskets used for research by individual trading desks. Their data enables clients to track the performance of portfolios, test and backtest trading strategies, and keep a finger on the pulse of markets worldwide. They’re subject matter experts, process engineers, project managers, data analysts, and customer service professionals, and they work closely with Product, Engineering, Enterprise, News, and several teams within Global Data to ensure the quick and accurate publication of the data our clients want and need.

The Role

Their team is looking for a data analyst with strong data engineering skills to take a key role in advancing their automation efforts. You’ll learn about their product and providers, but the balance of your efforts will go toward executing database migrations and creating and managing data pipelines. We’ll expect you to identify opportunities to improve our ETL processes, refine our business intelligence, bring in new business, provide accurate and timely customer support, and create premium content and services for our clients.

You’ll need to have:

    • Two years’ work experience in finance, engineering, technology, or a related field
    • Applied experience in a programming language such as Python, R, or Java, with a corresponding project portfolio
    • Strong written and verbal communication skills
    • Strong project management skills
    • The desire and ability to learn quickly on the job
    • Legal authorization to work full-time in the United States and will not require visa sponsorship now or in the future

They’d love to see:

    • Experience with the Bloomberg Professional Service
    • Experience with the Bloomberg Global Data Tech Stack (BAIT, BCOS, BBDS, DFR, DTP, EHUB, GDW) or comparable open-source technologies (Apache, AWS, Kafka, microservice architectures)
    • Experience with Python and the Python scientific stack (pandas, numpy, scikit-learn)
    • Familiarity with software engineering best practices including version control with Git/GitHub, testing, continuous integration
    • Familiarity with statistics, data analysis, and data visualization
    • Financial knowledge, notably of equity and fixed income markets

If this sounds like you:

Apply! If they think you’re a good match, they’ll get in touch to let you know the next steps.

They strongly encourage applications from populations traditionally underrepresented in finance and technology—please don’t self-reject! They are an equal opportunity employer and do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

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