Data Science Product Specialist - Enterprise Data

What is Enterprise Data? Bloomberg's Enterprise Data department develops data offerings that are considered best in class by the financial markets community. Across real time market data, reference data, historical pricing data, fundamentals and outstanding analytics we offer: - The most comprehensive and highest quality content in the industry - Distribution platforms that are flexible, reliable, fast, and easy to onboard - Easy to use data that is ready for analysis These data products serve as a critical foundation for decision-making across the front, middle, and back offices of major financial firms globally. The Role: Financial firms are purposefully embracing data science and machine learning techniques into their workflows. Motivated by increasingly sophisticated competition or cost savings, data science and machine learning have become a critical aspect of our customers' business strategies. Bloomberg wants to be the leader in analysis-ready data that allows clients to focus on critical activities such as alpha discovery, insight generation, back testing and creating advanced analytics solutions rather than data ingestion and normalization. You will play a significant role in helping customers and Bloomberg, together, achieve success. As hands-on liaison between Bloomberg product development teams and the data science teams at our customers, the Data Scientist will provide expert technical design, data science thought leadership, and Bloomberg recommended standard methodologies as customers develop solutions on premises or in the public cloud. The ideal candidate will be a customer focused data scientist with advanced technology skills that seeks opportunities to get their hands dirty while confidently working with clients to design and build solutions that will best demonstrate Bloomberg content and technology in conjunction with modern data science tools and workflows. Your expertise will directly contribute to the success of leading financial firms, reinforcing Bloomberg Enterprise Data's reputation as a trusted partner in the industry. We'll trust you to : - Lead deep technical discussions with customers, vendor partners, and Bloomberg colleagues from Product, Sales, Quant Research & Development, Engineering, and Client Services - Efficiently communicate sophisticated statistical and technical concepts with various audiences - Serve as subject matter authorities in demonstrating advanced data science workflows and technologies for financial markets use cases - Engage with customers as part of their solution creation team - Expertly make recommendations (based on standard methodologies) to customers and partners - Develop collateral including tutorials, sample code, reference implementations, and presentations that will be used by data science practitioners as well as executive decision makers - Provide feedback to Product, Quant, and Engineering teams to help shape product strategy and execution roadmap - Balance hands on work with a desire to keep up with trends You'll need to have? -5 Years of experience professional experience within financial services - Good knowledge of financial markets, quantitative strategies, and major investment asset classes - Understanding of a wide range of statistical models (e.g. regression, decision trees, artificial neural networks) and their underlying assumptions - Good programming skills in Python and SQL. Knowledge of other commonly used languages for data analysis is a plus - Experience with applying data science / quantitative / time series modeling to real world, financial use cases commonly deployed at financial market firms - Knowledge of leading open source data analysis tools and machine learning libraries - Experience in crafting technical documentation and presentations (white-board, small team, broad audience) and the ability to present to a technical and non-technical audience. - Entrepreneurial mindset and comfortable to work in a non-hierarchical, large global organization where interaction with senior management is required - Proven ability to build and maintain strategic relationships with clients' data science teams, ensuring that clients' data science needs are understood and communicated back the product management team - Passion for constant learning - Ability to travel We'd love to see: - Experience applying advanced machine learning to large scale, financial modeling problems - Master's degree or Ph.D. in a quantitative discipline - Knowledge of AWS, GCP, and/or Azure data science and machine learning services - Experience with tools and frameworks enabling large scale data analysis (e.g., Spark) - End-to-end knowledge of the data science problem, including large scale data and data pipeline management - Understanding of financial markets, banking, asset management, hedge fund, and/or the trade life cycle