CIB-Data Scientist –Associate.
Company Name: JP Morgan
Location: Columbus, Ohio, US
Date Posted: 10th Jun, 2017
- 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.
- The Data Scientists in this role will be leading small teams that develop innovative analysis. They will work closely with their teams, the Data Science lead and business analysts and software engineers within NPD to contribute to the advanced data analytics efforts of the New Product Development group.
- Will 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 and data mining tasks on diverse datasets from 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)
- Professional experience as a data scientist or a related software engineering role
- Experience leading the development of data science projects and coordinating the activities of small teams with deep technical and analytical skills.
- Doctoral degree, or equivalent experience, in mathematics, computer science, physical sciences or other quantitative discipline
- Thorough understanding of probability and statistics, Bayesian methods, time series analysis
- Expertise in theory and practice of Statistics, Empirical Data Analysis, Machine Learning and Natural Language Processing
- Experience and in-depth knowledge of Python and other modern programming languages
- Experience in at least one specialized statistical computing environment, preferably R
- Experience in practical data processing, data mining, text mining and information retrieval tasks
- Experience of scalable data management tools including Relational and NoSQL databases, Big Data architectures a strong plus
- Knowledge of Python’s data analysis and machine learning libraries a strong plus
- Great communication skills, team player, self-starter, self , demonstrated strong work ethic
- Desire to use modern technologies as a disruptive influence within the Finance domain