Research Engineer, Portfolio Management Group (PMG Tech), Associate

As a Research (AI) Engineer, you will partner with RQA, PMG Tech, and business stakeholders to develop data workflows, analytics solutions, and artificial intelligence-assisted capabilities that transform risk and quantitative challenges into actionable insights.

Embedded within a PMG Tech Pod, a business-focused, cross-functional team, you will collaborate with risk managers, quantitative analysts, artificial intelligence leads, and engineers. You will deliver high-quality data assets, analytical tools, and technology solutions that support risk management and informed decision-making.

This role requires an understanding of business problems and risk workflows, along with the ability to translate requirements into scalable data solutions. You will use Python, Structured Query Language (SQL), cloud data platforms, workflow orchestration, and visualization tools to develop and operate data-intensive applications. You will also apply data quality practices, continuous integration and continuous delivery processes, and data operations to create reliable, production-grade solutions.

Your responsibilities

In every role at BlackRock, you'll be expected to apply sound judgement and critical thinking to solve complex problems, adapt as the business evolves, and combine the curiosity to explore new approaches and technologies with the rigor to challenge the results. The scope of this role also includes the following responsibilities:

• Build and maintain web-harvesting processes, data pipelines, transformations, and workflows that support research hypotheses and data analysis.
• Develop platform capabilities that source high-quality data and create scalable, reliable, and maintainable data solutions.
• Create research utilities, prototypes, dashboards, and exploratory tools that support insight generation and research workflows.
• Engage with investors, researchers, risk managers, and quantitative analysts to understand their workflows and translate business requirements into effective data solutions.
• Collaborate with core engineering teams to adopt data-extraction and data-management capabilities that accelerate investment research.
• Partner with artificial intelligence leads to source data and build applications that supplement research with artificial intelligence-assisted insights.

Your experience

• Strong programming capabilities in Python and Structured Query Language, supported by analytical thinking and effective problem-solving skills.
• Demonstrated experience in data engineering, data analytics, or the development of data-intensive applications.
• Knowledge of, or curiosity about, investment research and risk-management workflows or similar domains.
• Proven ability to collaborate effectively across engineering, research, and business teams and translate requirements into scalable technical solutions.
• A bachelor’s or master’s degree in computer science, data science, data engineering, or a related field.
• Experience with web-harvesting techniques and cloud data platforms such as Snowflake, BigQuery, Google Cloud Platform, and Google Cloud Storage.
• Exposure to artificial intelligence and machine learning tooling, large language model experimentation, retrieval-augmented generation, summarization, and question-and-answer applications. Experience with dashboards, notebooks, lightweight research tools, enterprise-grade container orchestration platforms supporting declarative infrastructure and horizontal scaling, or directed acyclic graph-based workflow orchestration frameworks for data and batch processing is beneficial.