Business Banking - Data Scientist [multiple Positions Available]

JPMorgan Chase JPMorgan Chase · Banking · Plano, TX +1 · Consumer & Community Banking

Data Scientist role at JPMorgan Chase focused on developing and deploying machine learning models for financial prediction, trend identification, risk analysis, and anomaly detection within business banking portfolios. The role involves data processing, wrangling, ETL, automation, and leveraging visualization tools. Requires experience with Python, scikit-learn, SQL, and various BI software.

What you'd actually do

  1. Develop and deploy machine learning models to predict financial outcomes and identify trends.
  2. Perform risk-based analyses to identify trends within client portfolios.
  3. Utilize anomaly detection techniques to both ensure data integrity and drive decision making efforts.
  4. Automate data extraction, cleaning, transformation and loading processes to enhance efficiency.
  5. Leverage data visualization tools to present insights to stakeholders.

Skills

Required

  • data processing
  • advanced data analysis
  • insight generation to power data visualization solutions using Tableau, SAP Business Intelligence software, and Power BI
  • Executing complex data wrangling using SQL
  • Integrating data using ETL processes
  • Data automation using MySQL and SAP ERP software
  • Analyzing data and statistics to assess and quantify risk to inform business strategies
  • Automating data processes, statistical analysis, and spatial analytics using Python v3.8 and python packages including scikit-learn version 0.20.3, statsmodels, and ArcGIS Pro 2.6
  • Predictive modeling and outlier detection using techniques such as Random Forest, Local Outlier identification, Isolation Forest, or Multivariate regression

Nice to have

  • web technologies to optimize data visualization

What the JD emphasized

  • predict financial outcomes
  • identify trends
  • anomaly detection techniques
  • Automate data extraction, cleaning, transformation and loading processes
  • data processing
  • advanced data analysis
  • insight generation
  • data wrangling
  • ETL processes
  • Data automation
  • Analyzing data and statistics
  • quantify risk
  • Predictive modeling
  • outlier detection

Other signals

  • Develop and deploy machine learning models
  • predict financial outcomes
  • identify trends
  • risk-based analyses
  • anomaly detection techniques
  • Automate data extraction, cleaning, transformation and loading processes
  • Predictive modeling
  • outlier detection