Senior Data Management Professional - Content Acquisition Business Intelligence

Senior Data Management Professional – Content Acquisition Business Intelligence

Location:

New York

Business Area:
Data

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Bloomberg runs on data. Our products are fuelled by powerful information. We combine data and context to paint the whole picture for our clients, around the clock – from around the world. In Data, we are responsible for delivering this data, news and analytics through innovative technology – quickly and accurately. We apply problem‑solving skills to identify innovative workflow efficiencies, and we implement technology solutions to enhance our systems, products and processes – all while providing platinum customer support to our clients.

As part of the Content Acquisition (CA) department, we’re responsible for supporting the development, enablement, and implementation of data management protocols that enable the delivery of “ready‑to‑use” data.

What’s the role?

We are looking for a Senior Data Management Professional to join our team within Content Acquisition. You will work with our partners to turn data into clear, useful insights. Examples of insights might include: understanding the value of our existing data sets more clearly, identifying accounts / data sets that may warrant attention, or prioritizing how resources are allocated.

Senior Data Management Professionals help deliver these insights by coupling data literacy, technical skills and business insight to drive continuous improvement throughout the organization. You will develop and maintain quantitative tools to take care of product performance against business goals and outcome‑focused metrics. Senior Data Management Professionals will be at the forefront of our aim to create a center of excellence for business analysis and continuous improvement in Data.

• Analyse complex datasets to find opportunities and inform product, content, operations, and risk decisions
• Define, own, and track outcome‑focused metrics, using them to guide prioritisation and measure impact
• Build and iterate on datasets, dashboards and data workflows that enable decision‑making across product, operations, and risk
• Leverage user behaviour and data usage patterns to shape product direction, operational improvements, and risk mitigation strategies
• Partner with collaborators across CA to align on priorities, scope solutions, and deliver measurable outcomes
• Communicate insights and recommendations clearly to senior partners to influence decisions and drive action
• Own validation of initiatives through pre‑ and post‑launch activities (e.g., user interviews, surveys, performance tracking)
• Maintain clear and reliable documentation of datasets, methodologies, and analytical outputs

• 4+ years of experience in data science, data engineering, or business intelligence
• Bachelor’s degree or equivalent experience in Business, Finance, Technology, or a STEM‑related field
• Strong proficiency in SQL, Python, and Spark for scalable data processing, modeling, and analysis
• Experience working across the modern data stack, including storage, query engines, and visualisation layers (e.g., S3, Spark, Trino, Qlik, Streamlit, or similar)
• Experience translating business requirements into scalable, production‑grade data workflows, incorporating AI‑assisted development and agent‑based automation
• Hands‑on experience in areas such as machine learning, statistics, optimisation, product analytics, causal inference, and/or experimentation
• Demonstrated product thinking, with an ability to prioritise, balance trade‑offs, and focus on delivering measurable outcomes
• Demonstrable ability to manage and deliver multiple projects with solid attention to detail
• Solid eye for business with experience synthesising complex analyses into actionable recommendations

• Experience designing and scaling agentic, AI‑driven workflows using modern agent frameworks and orchestration tools (e.g., Lang Chain, MCP, or similar)
• Experience designing data‑driven workflows with an understanding of business process modelling (e.g., BPMN) and organisational change principles
• Experience deploying ML models in production, including monitoring and performance…