Description About this role Data Science at BlackRock
In February 2018, BlackRock builded the AI Labs, a new central Data Science and Engineering team with the purpose of accelerating innovation and technology in artificial intelligence, and to have firm-wide impact using data science to tackle strategic problems. The team is led by Dr. Rachel Schutt, and Professor Stephen Boyd, Samsung Professor of Engineering at Stanford.
The kinds of problems you'd be working on
Building a dynamic pricing and auto-bidding engine for the security lending business
Alpha generation: extracting signals from alternative data sets that provide investment opportunities to investors.
Predictive models in sales and marketing applications in order to anticipate client behavior and needs.
Natural language processing in order to extract and correlate n-grams from unstructured text including from financial reports, news, and contracts in order 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.
Automating repeatable tasks done by humans to free them up to work on the tasks that require their human intelligence
The firm-wide policy on algorithmic accountability and ethics of data science
The team you'd be part of In the first two years, the team has grown to 30+ data scientists and data engineers. The team works collaboratively; and multi-disciplinary with the following skills and capabilities: machine learning, statistical modeling, exploratory data analysis, natural language processing, data visualization, network/graph modeling, ETL, data pipelines, data architecture, communication, project / product management and strategy. We work with data from a wide variety of sources including text, news feeds, financial reports, time series transactions, user behavior logs, imagery, and real-time data.
AI Labs has offices in New York, Palo Alto, and Edinburgh. The team has several Stanford professors as senior advisors with world-class expertise in machine learning, statistics, optimization and stochastic control. These advisors include Emanuel Candes, Trevor Hastie, Robert Tibshirani, and Mykel Kochenderfer who dedicate time in our Palo Alto office and provide advice and mentorship for all members of the global team
We will be hiring a mix of tech leads and individual contributors with deep expertise in certain areas, as well as generalists. All individuals will be expected to have proven statistical/mathematical, and/or algorithmic/computational foundation and writing code is required. Each individual will be encouraged to contribute and lead based on their experience and expertise.
Your role and impact As Senior Software Engineer, you will improve BlackRock's product and services suite by crafting, growing and optimizing our data and data pipeline architecture. You will act as architecture lead on a multi-discipline, multi-region team of data scientists, engineers, and investment professionals on a corporate-wide set of client, investor, and operational problems. You will build and operationalize data pipelines to enable squads to deliver high quality data-driven product. You will be accountable for managing high-quality datasets exposed for internal and external consumption by downstream users and applications. The successful candidate will be highly motivated to be the lead architect that builds, optimizes, or redesigns data pipelines to support our next generation of products and data initiatives.
Lead in the creation and maintenance of optimized data pipeline architectures on large and sophisticated data sets that meet BlackRock business requirements.
Act as lead to Identify, design, and implement internal process improvements and relay to relevant technology organization.
Work with stakeholders to assist in the data-related technical issues and support their data infrastructure needs.
Automate manual ingest processes and optimize data delivery subject to service level agreements; work with infrastructure on re-design for greater scalability.
Keep data separated and segregated according to relevant data policies.
Work with data scientists to develop data ready tools to support their job.
Assist 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 vital.
6+ years of professional experience in Software Engineering in an enterprise level environment
Experience with full stack software development using Python or Java
Experience with building and optimizing 'big data' pipelines, architectures, and data sets is preferred
Working SQL knowledge and experience with relational databases
Experience with Hadoop, Spark, or Kafka is a plus
Experience with Amazon AWS and Google Cloud Platforms is a plus
Interested? Hit apply!
Our benefits To help you stay energized, engaged and inspired, we offer a wide range of benefits including a strong retirement plan, tuition reimbursement, comprehensive healthcare, support for working parents and Flexible Time Off (FTO) so you can relax, recharge and be there for the people you care about.
BlackRock's purpose is to help more and more people experience financial well-being. As a fiduciary to investors and a leading provider of financial technology, we help millions of people build savings that serve them throughout their lives by making investing easier and more affordable. For additional information on BlackRock, please visit www.blackrock.com/corporate | Twitter: @blackrock | LinkedIn: www.linkedin.com/company/blackrock
BlackRock is proud to be an Equal Opportunity and Affirmative Action Employer. We evaluate qualified applicants without regard to race, color, national origin, religion, sex, sexual orientation, gender identity, disability, protected veteran status, and other statuses protected by law. BlackRock will consider for employment qualified applicants with arrest or conviction records in a manner consistent with the requirements of the law, including any applicable fair chance law.