Bloomberg KYC - Data Science Product Manager

Careers at Bloomberg

New York

Posted Oct 12, 2017 - Requisition No. 62658

Know Your Counterparty (KYC) has evolved around regulatory requirement to understand the entities and individuals with whom one conducts business. While the steps imposed for KYC are commonly seen as painful, inefficient and unsustainable, the cost of delays and regulatory breaches can result in significant fines and opportunity cost.

Many have wondered if data and technology could be used to reduce the pain, the costs or the risk. Or better yet – to help firms improve their bottom line by pursuing opportunities faster, achieving scale or growing relationships?
The answer is yes.

Launched in 2015, KYC is a startup business within Enterprise Solutions that leverages Bloomberg's core strengths to help clients reduce time-to-trade, allowing them to make more money faster and to manage their KYC responsibilities more efficiently with lower operating costs and greater due diligence.
We are looking for a mixture between a product manager, data scientist, machine learning expert and engineer: someone who has passion for building and improving SaaS solutions informed by data. As a Product Manager you will use your understanding of our customers and apply your knowledge of Data Science and Machine Learning to solve their regulatory challenges.

You will work closely with engineers and data scientists to set the feature roadmap, prototype models, and enable sales. Most importantly, you will consistently deliver features that customers find valuable.

Classification techniques, especially text classification

Capabilities like advanced analytics, product insights, data science, test automation, project/portfolio management, lean-agile software development practices, and automated software development metrics are critical to our success.

We’ll trust you to:- Communicate with our cross-functional business partners to find the right questions, the right data and the right approaches needed to reach our goals

  • Identify and understand the regulatory landscape to drive product innovation
  • Analyze, visualize, and model job search related data. You will build and implement machine learning models to make timely decisions.
  • Collaborate with our Machine Learning engineers to innovate in the sourcing, management, and use of data
  • Own the vision for the product and bring new product features to market
  • Build a close working relationship with other Bloomberg product areas to incorporate their future direction into the overall evaluation of the business strategy and become an integral part of the Bloomberg regulatory solution
  • Meet with clients to obtain feedback and help drive product adoption
  • Communicate new features to internal and external stakeholders
  • Model interpretation and visualization: How do we help researchers, data scientists, and product developers understand the decisions that a model is making?

You’ll need to have: - Demonstrable experience as a Product Manager

  • Knowledge of the financial regulatory environment
  • Code literate in at least one language used by quants (e.g., Python or R)
  • Understanding of Statistical and Machine Learning techniques
  • Ph.D. or M.S. in a quantitative field such as Computer Science, Statistics, or Mathematics
  • Expertise in machine learning and statistical modeling
  • Passion to answer Product/Engineering questions with data
  • Experience in data collection, aggregation, analysis, visualization, productization, and monitoring of data science products
  • Ability to develop ML and/or NLP techniques and to apply them to real-world regulatory problems faced by our clients

If this sounds like you:

Apply if you think we're a good match and we'll get in touch with you to let you know next steps. In the meantime, check out http://www.bloomberg.com/professional.

We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, colour, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

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