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Digital Intelligence Developer
Ref No.: 17-02815
Location: New York, New York
Position Type:Contract
Pay Rate : $ 125.00 - 145.00 /Hour
Lead Investment Bank is seeking a Digital Intelligence Developer to work in a data driven Machine Learning Environment.

The Digital Intelligence team's mission is to deeply personalize the user experience of our millions of customers through the use of the firm's massive data, machine learning and  proprietary data platforms. Whether it's building a financial graph of consumers and small businesses, optimizing ad targeting on and paid media sites, recommending the most relevant hotels, or detecting fraudulent behavior, we work at the intersection of statistics, machine learning and engineering to tackle some of the most challenging and interesting problems you will find in digital banking, commerce and payment. Many companies claim that they work on "big data” and "data science”. We live and breathe them every day.

The ideal candidate for this leadership role will have the rare combination of data science, interpersonal, and business aptitude with a broad technical skillset touching one or more areas mentioned below. We are looking for those select few who thrive in a dynamic environment, have big ideas and goals, and believe in testing ideas rather than talking about them. They are hands-on, without needing an army of engineers or other data scientists to support them, and love learning new skills along the way. They feel comfortable working with a diverse team of UX designers, product managers, business leaders and engineers.  You will be joining one of the most elite data science teams on Wall Street: several of us have worked at other software companies and start-ups before joining the team.
  • Demonstrated a history of solving real-world problems in personalization, recommendation and search using applied math, statistics, machine learning, computer science and distributed computing.
  • Hands on experience with Apache Hadoop and Spark ecosystems of open-source tools and Client packages. Our data processing and modeling pipelines are built using Spark, MapReduce, Hive, Kafka, ElasticSearch, HBase, Cassandra, and other open-source platforms.
  • Passionate about changing the financial lives of millions of people by making banking simple, personal and human, and by using data, algorithms and insights.
  • Strong background in statistics, modeling and optimization as demonstrated by either industry experience or coursework/academic research.  Participation in KDD and Kaggle competitions will be a big plus.
  • MS/PhD in a quantitative discipline such as Statistics, Physics, Economics, Applied Math, Computer Science, Operations Research, or Computational Sciences, with coursework and projects in machine learning and data analysis.  Publications in top machine learning, AI or data science conferences and journals are highly desirable.
  • Fundamental understanding of algorithms that build recommendation systems, interest graphs, ad targeting models, trend analysis, and fraud/anomaly detection using online and offline features. A big part of the role is to be able to ask open-ended questions, explore new ideas, and choose appropriate techniques for solving a given problem, rather than using packages as a black box to a known problem.
  • Familiarity with A/B testing is a big plus, especially if you have experience in improving online/mobile product features by running customer/cookie-level experiments.
  • Must be able to write clean and concise code in at least two of the following: R, Python, Java, and Scala. Our interview process includes writing some code to solve a problem on the whiteboard.
  • You are curious, have a research mindset, love bringing logic and structure to loosely defined unstructured problems and ideas. You hold yourself and your teammates to a high bar, and take great pride in your attention to details. You inspire us to aim higher.
Third Party Applications Not Accepted