Senior Data Scientist

PayPal PayPal · Fintech · Chicago, IL +1 · Data Science

Senior Data Scientist at PayPal in Chicago, IL, focusing on developing and implementing advanced data science models and algorithms for financial data. The role involves deep-dive analyses, A/B testing, financial projections, and identifying new opportunities using data analytics. Responsibilities include collaborating with stakeholders, mentoring junior data scientists, and ensuring data quality. Requires a Master's degree or equivalent with 2 years of experience, or a Bachelor's degree with 5 years of experience, with specific skills in machine learning on financial data, default modeling, SQL/SAS, PySpark/Spark, AWS, Snowflake, Python, Tableau, and Agile methodologies.

What you'd actually do

  1. Lead the development and implementation of advanced data science models, algorithms, and data visualization tables.
  2. Research the latest trends, technologies, tools, and methodologies in Data Science.
  3. Perform deep-dive analyses, including causal inference analysis, A/B testing, and financial projections, to translate ambiguous, unstructured business problems into actionable, data-driven analyses that drive product decision-making.
  4. Use data analytics to identify new opportunities and ensure continuous improvement to the team’s KPIs and targets.
  5. Collaborate with stakeholders to understand requirements and identify/resolve complex data challenges affecting the user experience.

Skills

Required

  • Machine learning algorithms (Random Forest, XGBoost)
  • Financial data analysis
  • Causal inference analysis
  • A/B testing
  • Financial projections
  • SQL
  • SAS
  • PySpark
  • Spark
  • Python
  • AWS
  • Snowflake
  • Tableau
  • Scrum
  • Agile

Nice to have

  • Mentoring junior data scientists

What the JD emphasized

  • Applying machine learning algorithms (including Random Forest and XGBoost) on financial data for business insights (2 years)
  • Developing and recalibrating regression-based default models for financial portfolios (2 years)
  • Conducting analysis using SQL/SAS in database/server for large-scale data analysis (2 years)
  • Conducting data manipulation and transformation over complicated data structure using PySpark/Spark (2 years)
  • Building automated pipelines for SQL script on AWS and Snowflake (2 years)
  • Developing, testing, and running script and data pipelines in Python on cloud environments using distributed computing clusters (2 years)
  • Building and deploying automated dashboards and benchmarks for risk monitoring using Python, Tableau, and Snowflake (2 years)
  • Executing complicated models and maintain key documentation in production environment on cloud (2 years)
  • Conducting investigation on individual customer profile and complaints using various tools, including Python, Excel, Snowflake (2 years)

Other signals

  • Develop and implement advanced data science models and algorithms
  • Perform deep-dive analyses, including causal inference analysis, A/B testing, and financial projections
  • Use data analytics to identify new opportunities and ensure continuous improvement to the team’s KPIs and targets
  • Collaborate with stakeholders to understand requirements and identify/resolve complex data challenges affecting the user experience