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Associate- Data Science India - GMG- Bangalore

Req #: 170094395
Location: Bangalore East, KA, IN
Job Category: Sales/Trading/Research
Job Description:
About J.P. Morgan Corporate & Investment Bank

J.P. Morgan’s Corporate & Investment Bank (CIB) is a global leader in Banking. The world’s corporations, governments and institutions entrust us with their business in more than 100 countries. The Corporate & Investment Bank supports our clients around the world providing strategic advice, raising capital and managing risk.

Who we are

We are a small, focused team of passionate engineers, data and business people set on creating and building products that transform the way we and our clients do business.

Sure, we are part of a large financial services firm operating in a highly-regulated environment, and that means we are not as flexible or agile as your average company – let alone a startup. But we are careful stewards of our clients’ trust and money and combine creativity and speed with discipline and awareness. It also means that what we build matters and have huge impact; our products and solutions will reach our 1000s of clients around the world, and affect how J.P. Morgan does business – from trading securities in multiple markets to moving trillions of dollars a day. We won’t build it unless we know it is scalable.

We are obsessed with effectiveness, productivity and efficiency; if we find an issue or broken process, we fix it. We work with the right tools, make decisions quickly, and only pursue those ideas that can scale and meet our clients’ and our business’ critical needs.

Why join?

This is a fascinating time in our industry. By now, it’s a cliché that Banks will have to embrace technology and innovation if they are to thrive in the years to come. We are already bought into this and are committed to show that we can do it, and are looking for others to join.
 
You will:
 
  • Work on some of the most complex problems imaginable at the intersection of two dynamic industries – finance and technology.
  • Interact with insanely large and fascinating data currently not available anywhere else.
  • Develop products that can change the way 1000s of clients operate, and how Banking is done today.

 
An analyst will join a small team, and participate as a group in projects executed on by the New Product Development (NPD) team. You will work closely with the head of Data Science, your team leader and other business analysts and software engineers within NPD, to help build a foundation of state-of-the-art technical and scientific capabilities to support a number of ongoing and planned data analytics projects.
  • Build an in-depth understanding of the problem domain and available data assets
  • Research, design, implement, and evaluate machine learning approaches and models
  • Perform ad-hoc exploratory statistics /data mining tasks on diverse datasets - small scale to “big data”
  • Participate in data architecture and engineering decision-making to support analytics
  • Take initiative in evaluating and adapting new approaches from data science research
  • Investigate data visualization and summarization techniques for conveying key findings
  • Communicate findings and obstacles to stakeholders to help drive the delivery to market
  • Code your solutions (this is a hands-on position requiring strong programming skills)
Key Requirements:
  • Professional experience as a data scientist or a related software engineering role
  • Graduate degree (MS) in mathematics, computer science or other quantitative discipline
  • Thorough understanding of probability and statistics, Bayesian methods, time series analysis
  • Strong programming skills (in any language)
  • Great communication skills, team player, self-starter, demonstrated strong work ethic
  • Desire to use modern technologies as a disruptive influence within the Finance domain
 
Preferred
 
  • Expertise in Statistics, Empirical Data Analysis, Machine Learning or Natural Language Processing
  • Experience and in-depth knowledge of Python and other modern programming languages
  • Experience in a specialized statistical computing environment, preferably R
  • Experience in practical data processing, data mining, text mining and information retrieval tasks
  • Experience in scalable data management tools - Relational and NoSQL databases
  • Knowledge of Big Data architectures a strong plus
  • Knowledge of Python’s data analysis and machine learning libraries a strong plus
 
 
 
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