JPMorgan Decision Scientist- Senior Associate 

United Kingdom, England, London 

873122147

As a Senior Associate 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 spec customisation requirements:

• Job responsibilities:
  • Utilise advanced data science and machine learning methodologies to solve complex real-world problems
  • Collaborate with data and machine learning engineers to deploy models within the cloud infrastructure
  • Perform quantitative ad-hoc analysis and present findings to the stakeholders in a clear, logical and persuasive manner, illustrating them with effective visualisations
  • Collaborate with business partners and domain experts to identify business opportunities and understand business problems
• Required qualifications, capabilities and skills
  • Masters in a STEM subject (e.g. Mathematics, Computer Science, Engineering, Physics) and 3-5 years of industry experience, or Ph.D. in a STEM discipline and 2 years of industry experience.
  • Solid background in probability, statistics, data science and machine learning methodologies (e.g. supervised/unsupervised learning, linear regression, random forests, xgboost)
  • Familiarity with Python, SQL and open-source libraries for data science and machine learning (e.g., numpy, pandas, scikit-learn, pyTorch, tensorflow)
  • Ability to work both independently and in a highly collaborative team environment
• Preferred qualifications, capabilities and skills
  • Working knowledge in one or more of these areas: Natural Language Processing methodologies (e.g., transformer-based architecture), probabilistic programming, causal inference techniques, recommender systems, time series forecasting, explainability in machine learning.
  • Familiarity with one or more of these libraries: OpenAI APIs, huggingface, pystan, pymc, statsmodels, sktime, shap, pyspark, dask, xgboost
  • Advanced SQL querying skills
  • Ability to develop and debug production-quality code