Associate - Data Services Engineering – Data Scientist / Data Engineer
- New York, NY, USA
- Permanent, Full time
- 29 Sep 16
Associate - Data Services Engineering – Data Scientist / Data Engineer
BlackRock Data Services - Data Scientist / Data Engineer
New York, NY
BlackRock is one of the world's preeminent asset management firms and a premier provider of global investment management, risk management and advisory services to institutional, intermediary and individual investors around the world. BlackRock offers a range of solutions - from rigorous fundamental and quantitative active management approaches aimed at maximizing outperformance to highly efficient indexing strategies designed to gain broad exposure to the world's capital markets. Our clients can access our investment solutions through a variety of product structures, including individual and institutional separate accounts, mutual funds and other pooled investment vehicles, and the industry-leading iShares® ETFs.
Business Unit Overview:
BlackRock Data Services (BDS) is BlackRock's main data processing and quality control group - roughly 750 people worldwide, ensuring our data is loaded and/or computed, quality-controlled, and delivered to our users and other downstream systems in the appropriate formats - completely, accurately and on time.
This includes data on clients, portfolios, index portfolios, positions, security terms and conditions and pricing, portfolio net asset values and cash, risk and returns calculations, compliance with investment guidelines and more. Our production and quality control platform currently analyzes tens-to-hundreds of millions of data points daily - and more than that on a weekly/monthly frequency.
BDS's Data Engineering group continually advances this platform, through projects large and small. Our work generally includes a combination of process automation and re-engineering, software architecture and development, and researching and improving the business logic that flags, investigates and resolves data issues.
Job Description and Responsibilities:
The Operations Analysis team within Engineering works with BDS management and staff to:
• Understand BDS teams' business needs, their operational processes and their inter-relationship with other teams' functions and processes;
• Provide transparency into the department's operations to our staff, management and upper management using process diagrams and key measures of operating effectiveness (KPIs/KRIs and more);
• Identify the best areas to focus our department's improvement efforts;
• Research, prototype and deliver new products, technologies and techniques to better understand and run our business;
• Provide consulting services in our areas of expertise (data science / machine learning, operations analysis and improvements)
• Foster an understanding of modern technologies, methodologies, architectures and best practices that will continue advancing our culture of constant improvement.
Current focuses include:
• Defining our next-generation data processing and quality control platform.
1. Big Data technologies look to play a part in this; our current Big Data technology stack includes Spark, SnackFS, Cassandra, HDFS, Zookeeper, Hive, Mesos and more. Java/Scala and python being our development languages of choice.
2. Using data science / statistical modeling techniques and analyzing end-to-end data flows and business processes to make quality control more holistic and more scalable.
• Providing a data science "self service" tool to our data-savvy business users.
Users research, build and deploy their own models - engaging us as advisors, letting us scale.
• R&D in technologies and techniques of interest to our operations - current interests include Process Mining, Robotic Process Automation, a variety of NLP-related technologies, and more.
Our core knowledge base includes applied math and statistics, data science and machine learning, software development, operations research, and knowledge of the investment process - from pre-trade risk analytics and decision support to trade processing and subsequent analysis and attribution of returns.
The interdisciplinary nature of our work and the breadth of business functions we partner with give our staff an excellent introduction to much of the BlackRock organization as well as flexibility in longer-term career growth opportunities.
Advanced degree in Computer Science, Applied Mathematics or Statistics, Operations Research, and/or science or engineering discipline strong in these areas is required.
We are looking for candidates with 4 to 10+ years of strong experience in one or more of these areas:
1) These aspects of the data lifecycle, at an enterprise level:
o Data acquisition, creation, storage - we are particularly looking for people with experience in implementing Big Data technologies successfully in an enterprise;
o Knowledge discovery - in particular, people with advanced knowledge in entity and relationship extraction from unstructured data;
o Data cleansing and quality control techniques - in particular, experience developing or integrating software allowing for flexible and scalable data transformation. In the area of quality control, we are particularly interested in people who have implemented strong anomaly/outlier detection;
o Data analytics - in particular, looking for people who have strong backgrounds in statistics, machine learning and similar technologies. Must have experience in implementing predictive and/or prescriptive data analytics solutions;
o Data visualization and reporting - in particular, knowledge of tools that are cost-effective and make it easy for end users to better understand and produce reports and graphs.
Candidates who have made significant contributions to building robust data processing and analytics pipelines are a strong plus. Candidates with strong knowledge of modern Big Data / Fast Data technology stacks are a strong plus.
2) Fast and solid software development (design / development / testing / documentation / support) - in particular, strong knowledge of algorithms and object-oriented programming is a must.
o Java is BlackRock's main development language. C++ background is valued.
o Python, Scala and perl are our scripting languages of choice - but you must be capable of much more than simple scripting.
Candidates with a strong knowledge of software development best practices, design patterns and process design are a strong plus.
Candidates with knowledge of Six Sigma, Lean and similar methodologies, especially as applied to Information Management, are a strong plus.
Experience in the finance industry or knowledge of financial products, markets and analytics is a plus.
A successful candidate must:
• Have a strong passion to understand how things work and to make them work better.
• Have a strong technical background, including some software development; at a minimum, you will be expected to install, configure and evaluate software products and to look at code to understand how some of our software works. Ideally, you will be able to develop software BlackRock staff (and potentially clients) can use as part of their workflows.
• Be a very strong problem solver; this often includes working with others to learn more about a problem, but can also include self-motivated research into a technology or a business process.
• Be able to absorb a high volume of knowledge and data quickly.
• Possess very good written and verbal communications skills, including creating and giving presentations to all levels of the organization.
• Enjoy a fast-paced, high-intensity, cross-functional environment.
If interested, all candidates MUST apply online through our career site at www.BlackRock.com (use Requisition ID 161742) and submit a copy of your most recent resume and cover letter via email to firstname.lastname@example.org (Subject: "Data Scientist / Data Engineer position").
BlackRock is proud to be an Equal Opportunity/Affirmative Action Employer -- M/F/D/V
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, disability, veteran status, and other statuses protected by law.