Data Scientist – ETL Pipelining
Posted Jan 27, 2021 - Requisition No. 88504
At Bloomberg, our products are fueled by powerful information. We combine data and context to paint the whole picture for our clients, around the clock – from around the world. In Global Data, we’re responsible for delivering this data, news and analytics through innovative technology - quickly and accurately.
Our Global Data team drives the algorithms and analytics at the core of what we do. Working across industries and asset classes, we draw on expertise from all backgrounds to identify the most impactful insights for our clients. We build on our knowledge of data trends to determine how customer needs might change over time, and code the foundation to support those changes.
Whether it’s providing datasets to track market-moving economic events, or quantifying extreme weather effects on companies, we write the programs, analyze patterns, and make recommendations to grow business success across the firm. The entire organization utilizes Global Data to forecast, set, and achieve their own goals. Our work leads directly to client satisfaction, which contributes to Bloomberg’s profitability and ability to keep innovating.
We’re looking to hire qualified professionals into either our Economics Data Team or our Geospatial Data Team. Both of these teams sit under our Global Data umbrella, and work to synthesize meaningful solutions for our clients. These teams are looking for professionally experienced individuals to join their ranks and add on to the great wealth of knowledge we have in-house.
We’ll trust you to:
- Create pipelines: identify opportunities and build flexible automated solutions for data standardization, ETL pipelines, and human-in-the-loop data processing
- Improve quality: Design, develop, and deploy data quality rules written in Python to drive quality improvements and standards across the team, improving areas such as accuracy, completeness, consistency, reliability and more
- Drive operations: draw on your scripting and programming skills to report on project progress, create data visualizations, and propose new methods of analysis
- Implement innovation: analyze metadata and current processes to find opportunities for improvement
- Influence priorities: Review market conventions and data relationships to set rules for data validation
- Achieve your purpose: optimize processes, lead projects, and improve the quality of the products sought by internal and external end-users
You’ll need to have:
- A BA/BS degree or higher in Computer Science, Mathematics, or relevant data technology field, or equivalent professional work experience in software development, data engineering, data science or information technology
- 2+ years of programming and scripting experience in a Python production environment
- 2+ years of experience with SQL & NoSQL database systems
- Proficiency with git, unix, python ecosystem, web services and API usage
- Consistent track record of using technology to innovative data products and processes
- Proficiency using data and statistical modeling and machine learning methods to solve real world problems
- Legal authorization to work full-time in the United States and will not require visa sponsorship now or in the future
Does this sound like you?
Apply if you think we're a good match. We'll get in touch to let you know what the next steps are.
Bloomberg is committed to diversity. It drives our innovation. At Bloomberg, you'll have the opportunity to go above and beyond and to take risks. You'll be a part of an organization that is entering new markets, launching new ventures, and pushing boundaries. Our ever-expanding array of technology, data, news, and media services champions innovation and empowers clients -- and offers nearly limitless opportunities for career growth.
We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. We bring out the best in each other.