Head of Enterprise Data Science

Key Skills

Apache Hadoop, C Programming, C++, Data science techniques, Java Programming, Machine learning techniques, MapReduce, Python Programming, PyTorch, R Programming, Scala Programming, SQL, TensorFlow

Job Description

We’re Bloomberg Enterprise Data - fast paced, innovative and rapidly growing. We deliver an unparalleled and ever-growing breadth and depth of enterprise content to the world's leading market participants.

We are looking for a hands-on manager for our Data Science function within the Enterprise Data division at Bloomberg LP. This team is responsible for building quantitative models to produce new and innovative data and analytics products using the latest machine learning techniques. Additionally, we have an aggressive roadmap of delivery for our portfolio of time series based data products designed specifically for the needs of our customer quant audience. We leverage a modern cloud based technology stack to facilitate the build out of these products.

As we continue to invest, we need a senior leader to identify new ways of leveraging our content and technology to extend our offerings.

We’ll trust you to:

• Manage teams responsible for large and complex analytical projects from data exploration, model building, performance evaluation and testing, leveraging the latest data science techniques
• Understand financial clients’ quantitative/research use cases and creating compelling solutions that address real client needs
• Lead discussions with senior client decision makers
• Advance best practices and provide thought leadership within data science and product teams
• Continually research and evaluate emerging technologies; stay current on published state-of-the-art methods, technologies, and applications and seeking out opportunities to apply them

You’ll need to have:

• 5 years of experience leading Data Science teams solving high impact business problems
• A Bachelor or Master’s degree in Science, Computer Science or related disciplines
• Experience with diverse technology applications and associated architectures
• Knowledge of and interest in structured financial data models and data driven requirements
• Experience working with Global Multidisciplinary Teams, (Sales, Technology, and Operations)
• Experience with applied statistics and quantitative modelling (e.g., regression, survival analysis, segmentation, experimentation, and machine learning when needed)
• Demonstrated ability to translate analytical insights into clear recommendations and effectively communicate them to technical and non-technical stakeholders including senior management 
• The ability to address multiple priorities in an extremely fast-paced environment
• Curiosity about the problem domain and an analytical approach 
• Strong focus on outcomes and delivery, balanced with a practical and hands-on approach to timely, regular incremental delivery of high quality revenue generating products

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.