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Digital Data Scientist

Req #: 170073690
Location: New York, NY, US
Job Category: Digital
Potential Referral Amount: 0 US Dollar (USD)

JPMorgan Chase & Co. (NYSE: JPM) is a leading global financial services firm with assets of $2.6 trillion and operations worldwide. The firm is a leader in investment banking, financial services for consumers and small business, commercial banking, financial transaction processing, and asset management. We serve millions of consumers in the United States and many of the world's most prominent corporate, institutional and government clients under our J.P. Morgan and Chase brands. Information about JPMorgan Chase & Co. is available at www.jpmorganchase.com.

 

Chase Consumer & Community Banking serves nearly 66 million consumers and 4 million small businesses with a broad range of financial services, including personal banking, investment advice, small business lending, mortgages, credit cards, payments and auto financing.   In recent years, we have undertaken a large-scale digital transformation initiative, building on the success of our current mobile and online service offerings.  The Digital team is responsible for building innovative platforms and developing new products that make banking and payment tasks simpler and more personalized for our customers, as well as deepen customer engagement and loyalty with more relevant offers and services. The ambition is to position Chase as the undisputed leader in digital financial services and payments, and to enable highly personalized, real-time experiences that customers increasingly expect.  We function similar to a fintech start-up in our brand new offices that inspire collaboration, transparency, agile development, and a fun working 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 chase.com/mobile 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 has deep skills in one or more areas mentioned below, and is passionate about solving real-world problems. 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.

·         You are 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.

 

·         Solid understanding of algorithms to 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.

 

·         Familiarity with Apache Hadoop and Spark ecosystems of open-source tools and ML packages very desirable. Our data processing and modeling pipelines are built using Spark, MapReduce, Hive and other open-source platforms.  You do not have to be an expert in these but we will help you to quickly ramp up on your Hadoop, Spark and MLlib skills in order to scale to petabytes of data that we analyze.

 

·         Must be able to write clean and concise code in at least one of the following: Python, 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 high.

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