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JPMorgan Data Scientist Lead - Chief 
United Kingdom, England, London 
312068316

26.06.2024

We’re looking for someone with considerable experience manipulating data sets and building statistical models, has a Master’s or PhD in Statistics, Mathematics, Computer Science or another quantitative field.

Job Responsibilities:

  1. Strong Programming skills using Python, Java, Java Scripts
  2. Strong in Statistics and probability: very well versed with
    1. Probability distributions
    2. Over and under sampling
    3. Bayesian and frequentist statistics
    4. Dimension reduction
    5. Linear regression
    6. Clustering
    7. Decision Trees
  3. Strong in Data wrangling and database management which involves process of cleaning and organizing complex data sets to make them easier to access and analyze. Manipulating the data to categorize it by patterns and trends, and to correct and input data values can be time-consuming but necessary to make data-driven decisions.
  4. Develop custom ML models and algorithms to apply to data sets and hands on experience in building various ML models like:
    1. Linear regression
    2. Logistic regression
    3. Naive Bayes
    4. Decision tree
    5. Random forest algorithm
    6. K-nearest neighbor (KNN)
    7. K means algorithm
    8. Ensemble models
    9. Simulation
    10. Scenario Analysis
  5. Knowledge and experience in statistical and data mining techniques: GLM/Regression, Random Forest, Boosting, Trees, text mining, etc.
  6. Mine and analyze data from company databases to drive optimization and improvement of product development, marketing techniques and business strategies.
  7. Develop company A/B testing framework and test model quality.
  8. Coordinate with different functional teams to implement models and monitor outcomes.
  9. Develop processes and tools to monitor and analyze model performance and data accuracy.
  10. Experience in Fine tuning the model

Required Qualifications:

  • Considerable experience manipulating data sets and building statistical models.
  • Master’s or PhD in Statistics, Mathematics, Computer Science or another quantitative field