As a Senior Data Scientist, you will act as technical lead to develop, build, evaluate and improve Blackrock’s data science and artificial intelligence services and products. You will have a leadership role on a multi-discipline, multi-region team of world-class data scientists, engineers, and investment professionals addressing large scale analytic challenges corporate-wide. Your position will define the analytical and statistical functions required to address the challenges of measuring data and analytical quality; building (NLP, Graph, Statistical) technology capabilities, and understanding the needs and behaviors of our end users and clients.
- Act as a lead to solve novel investment, client, or operational analysis problems. This can include problems in a multitude of areas including but not limited to:
- NLP such as extracting and correlating n-grams from unstructured text to drive contextual understanding in different business applications across the firm.
- Graph Analysis for path generation for data lineage/provenance, ontological development, or network analytics.
- Statistical analysis to generate predictive models in sales and marketing applications.
- Alpha generation: extracting signals from data sets that provide investment opportunities to business.
- Play a leading role in end to end analysis that includes data gathering, requirements specification, processing, analysis, algorithms, builds, code reviews, ongoing deliverables, and presentations for specific projects.
- Lead in prototype analysis and data pipelines iteratively that will lead to insights at scale.
- Lead in the development of holistic understanding of Blackrock data structures and metrics, advocating for changes to promote new product features or sales opportunities.
- Research and develop new analytic solutions and methods to directly improve Blackrock’s suite of products and services through creation of new models, features, or experimental design.
- Work closely with data engineering and infrastructure to build out end to end solutions.
- Lead in the development of business recommendations with effective presentation of findings at multiple levels of stakeholders using visual analytic displays of quantitative information. Communicate findings with stakeholders as necessary.