Data Science

Software Engineer / Research Scientist - Machine Learning Team

 
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Software Engineer / Research Scientist - Machine Learning Team

Location: New York City

Company: Bloomberg LP

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Bloomberg’s core product, the Terminal, is a must-have for the most influential people in finance. In addition to being the second largest producer of news in the world, Bloomberg ingests more than 1.5 million news stories per day from more than 120,000 different sources to help our clients stay in the know. This data would be unmanageable without our help. News stories move markets. We build machines that understand them.

Who are we? Bloomberg's Machine Learning Group - a group of scientists, researchers and software engineers who have a passion for solving complex data problems. We develop applications such as question answering, sentiment analysis of financial news, market impact indicators, social media analysis, topic clustering and classification, recommendation systems, risk analysis and predictive models of market behavior.

Who are you? A research scientist and engineer who wants to apply machine learning to solve challenging open-ended problems. You want to be part of a team making a big impact on the financial industry and are not afraid to get your hands dirty in data.

We'll trust you to:

  •  Design and build systems that solve difficult problems involving text, time series and other complex data sources
  •  Analyze Bloomberg’s unique data to build novel prediction models
  •  Write, test and maintain production-quality C++ and Python code
  •  Publish in leading academic venues and represent Bloomberg at industry conferences

You'll need to have:

  •  Strong Computer Science fundamentals (algorithms, data structures)
  •  Solid background in natural language processing and/or machine learning
  •  Industry experience programming in C++ and Python; working knowledge of STL & Boost
  •  Strong communications and interpersonal skills

We'd love to see:

  •  Strong mathematical background (probability and statistics)
  •  A PhD in Machine Learning or Natural Language Processing
  •  Publications in top-tier conferences or journals (ACL, EMNLP, ICML, NIPS, KDD)
  •  Experience with building machine learning models using time series data
  •  Industry experience developing latency sensitive applications
  •  Working knowledge of Spark

Senior Big Data Engineer - Latency Monitoring System

Senior Big Data Engineer - Latency Monitoring System

Location: New York

Company: Bloomberg LP

 
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You're a software engineer who has develops and integrates large systems with many parts, and can distribute data between those parts. You're interested in Big Data sets, performance analysis, and statistics. You enjoy working with low latency, high throughput systems, and are comfortable thinking about the distance between two cities in both miles and milliseconds. You're interested in using open-source technologies, but if it doesn't exist you're happy to build it.

If this sounds like you, then consider working on the Latency Monitoring System. We're building a system from scratch to explore the latency of market data delivery on Bloomberg's global network. You'll be involved nearly from the beginning, designing a system that helps both developers and business departments understand how data flows through our system and where we can improve. We're looking for someone who can contribute to all aspects of the system, from parsing to data storage to data analysis. You'll work with a small, flexible team on identifying how applications behave under load, which applications can be improved, and where the bottlenecks are.

We'll trust you to:

  •  Design and implement distributed data analytics systems, using Hadoop/Spark, Python, and C/C++
  •  Manage cloud resources in order to maintain resiliency and performance
  •  Effectively roll out new features using an Agile methodology
  •  Work with a small team on all parts of the system, from data capture to display
  •  Participate with the rest of the team in analyzing the latency data, finding bottlenecks, and proposing solutions

You need to have:

  •  2+ years experience with Hadoop and Spark
  •  2+ years experience with Openstack or Amazon EC2 (or equivalent)
  •  4+ years experience with Python
  •  BS or MS in Computer Science or equivalent experience
  •  Experience with GitHub and a solid understanding of core concepts with Git
  •  Familiarity with Linux
  •  A solid understanding of basic statistics and core computer science concepts

We'd love to see:

  •  A strong understanding of distributed computing
  •  Familiarity with web technologies, including NGinx, Flask, and REST APIs
  •  Experience with chef, puppet or ansible
  •  Familiarity with system administration tasks, such as managing services, hardware, and network configurations
  •  Prior experience working with trading or market data

Senior Data Science Platform Engineer

 
 

Senior Data Science Platform Engineer

Company: Bloomberg LP

Location: New York

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Bloomberg runs on data. It's our business and our product. From the biggest banks to the most elite hedge funds, financial institutions need timely, accurate data to capture opportunities and evaluate risk in fast-moving markets. With petabytes of data, our data science team is at the forefront of innovation in our business. We transform large amounts of structured and unstructured data such as text, time series, and events into machine-readable knowledge fueling applications and consumer decisions. The platform which supports these efforts is critical to its success.

That's where you come in. Working in a talented multi-disciplinary team, you will be responsible for the research, development, and stability of our next generation Data Science platform. This role offers the ability to truly innovate and invent, helping define the technical foundations of this groundbreaking system. Built with containerization and modern container orchestration systems on top of cutting-edge hardware, including GPU's, you will help build a system that rivals super-computing platforms across the world.

Our team:

The Data Science Infrastructure team is a new team which was established to build a platform supporting development efforts around data-driven science, machine learning, and business analytics. This is a very young team, enabling you to make a large impact by bridging advanced infrastructure with the worlds of Machine Learning and Data Science.

What's in it for you:

You'll have the opportunity to make key technical decisions which will bring this platform into the future. You'll be able to apply your existing knowledge while gaining experience in the areas of orchestration, containerization, GPU's, and data science. You'll have the opportunity to contribute to solutions that support new functionality within the Bloomberg Terminal, a leading driver of financial decisions around the world.

How we give back:

This new team will make extensive use of open source software. As part of that, we make a commitment to upstreaming features we'll be developing. Whether pushing bug-fixes upstream, developing new features, giving presentations at conferences and meetups, or collaborating with industry leaders, open source will be at the heart of this team. It's not just something we do in our free time, it is how we work.

We’ll trust you to:

  •  Interact with data scientists to understand their workflows and requirements
  •  Design and deploy solutions for problems such as high availability, elastic load distribution, and high throughput
  •  Automate operation, installation, and monitoring of data science ecosystem components in our infrastructure stack

You’ll need to be able to:

  •  Troubleshoot and debug run-time issues
  •  Provide developer and operational documentation
  •  Provide performance analysis and capacity planning for clusters
  •  Identify and perform OS and hardware-level optimizations
  •  Be organized and multitask in a faced paced environment

You’ll need to have:

  •  Experience programming in Python, Java, Scala, JavaScript, or Ruby
  •  Linux systems administration experience (Bash, Network, Filesystems)
  •  Experience with configuration management systems (Chef, Puppet, Ansible, or Salt)
  •  Experience with continuous integration tools and technologies (Jenkins, Git, Chat-ops)

We’d love to see:

  •  Experience building and scaling Docker based systems using Kubernetes, Swarm, Rancher, Mesos
  •  Experience configuring, deploying, managing Apache Spark, and Hadoop HDFS
  •  Experience working with authentication and authorization systems such as Kerberos and LDAP
  •  Experience working with GPU compute software and hardware
  •  Open source involvement such as a well-curated blog, accepted contribution, or community presence

If this sounds like you, apply! You can also learn more about our work using the links below:

Analytics Manager / Data Scientist

Location: Washington, DC Metro Area

Company: (Undisclosed)

Job Requisition Code: P-02

We are looking for an analytics manager to help us turn data insight into business strategy! The right candidate will have deep analytic expertise in extracting, cleaning, and modeling data to identify opportunities for improved customer acquisition, retention, and engagement.

RESPONSIBILITIES

Testing Pipeline

  • Brainstorm / gather hypotheses on customer facing tests
  • Model potential impact to prioritize product tests
  • Track test results, leading testing meetings to ensure clear communication
  • Make recommendations on go/no-go decisions for rolling out test more broadly based on analysis / feedback, determine additional testing that may be warranted
  • Make recommendations on go/no-go decisions for rolling out test more broadly based on analysis / feedback, determine additional testing that may be warranted
  • Manage learning library to document test impact

Marketing Analysis & Modeling

  • Own core customer models, including evolving methodology as operations or goals dictate, updating assumptions over time, and validating against actual results.
  • Own Unit Economics and Marketing Efficiency (by marketing channel, paid/organic sources)
  • Build and own a Customer Lifetime Value model (by plan type)
  • Build and own Cash Forecasting model based on Retention, New Customer Acquisition
  • Build dashboards and reports to surface data at the time of acquisition to improve the efficiency of our marketing efforts

Content and Product Analysis & Modeling

  • Build core KPIs around user engagement, establishing targets and benchmarks
  • Web engagement analysis via Google Analytics
  • Determine correlations between engagement KPIs and NPS scores with user retention
  • Identify actions correlated with churn and test strategies to abate churn (segment based)
  • Support Content team in their acquisition strategy by looking at null search results, customer engagement by content type and other analyses linked to content library

 

DESIRED EXPERIENCE

  • 3+ years of e-commerce / digital media analytics experience with demonstrated track record of manipulating large, complex data sets and using them to build sophisticated models
  • Expertise with advanced analytics software (more than just basic SQL experience), such as R, SAS, Stata, Python, SPSS, or other analytics tools
  • Experience with advanced statistical modeling techniques, including multiple regressions and machine learning models
  • Strong analytical skills and comfort breaking down and attacking open ended problems
  • Attention to detail and ability to manage tasks in a fast-paced technology-oriented environment
  • Desire to contribute to the hyper-growth and culture of a successful technology company