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JPMorgan Data Science Associate 
United Kingdom, England, London 
10536083

Yesterday

As a Data Scientist at JPMorgan Chase within the International Consumer Bank, you will be a part of a flat-structure organization. Your responsibilities are to deliver end-to-end cutting-edge solutions in the form of cloud-native microservices architecture applications leveraging the latest technologies and the best industry practices. You are expected to be involved in the design and architecture of the solutions while also focusing on the entire SDLC lifecycle stages.

Job responsibilities:

  • Collaborating with business partners, research teams and domain experts to understand business problems.
  • Providing stakeholders with timely and accurate reporting.
  • Performing ad hoc analysis based on diverse data sources to give decision-makers actionable insights about the performance of the products, customer behavior and market trends.
  • Presenting your findings in a clear, logical, and persuasive manner, illustrating them with effective visualizations.
  • Collaborating with data engineers, machine learning engineers and dashboard developers to automate and optimize business processes.
  • Identifying unexplored opportunities to change how we do business using data.

Required qualifications, capabilities and skills:

  • Advanced SQL querying skills.
  • Competent data analysis in Python.
  • Experience in taking business questions and using big data and statistics to arrive at an answer.
  • Experience with customer analytics such as user behavioral analysis, survey analysis, etc.
  • Demonstrated ability to think beyond raw data and to understand the underlying business context and sense business opportunities hidden in data.
  • Ability to work in a dynamic, agile environment within a geographically distributed team.
  • Excellent written and verbal communication skills in English.

Preferred qualifications, capabilities and skills

  • Distinctive problem-solving skills and impeccable business judgment.
  • Familiarity with machine learning.