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Senior Data Scientist
  • Python
  • Spark
  • SQL
  • Machine Learning
  • Big Data
  • Data Analysis
  • Excel
  • Data Mining
  • Modeling
  • Deep Learning
  • Bayesian
Arlington, VA
131 days ago

Arlington, VA
Primary Responsibilities:
  • Build predictive models including but not limited to credit risk, marketing, fraud, and offer acceptance propensity
  • Perform through testing and validation of models and support various aspects of the business with data analytics; I.e., experience with data and model governance
  • Identify new data sources/patterns that add significant lift to predictive modeling capabilities; ideally come in with existing knowledge about relevant datasets/services, to leverage
  • Research, design, implement and validate cutting-edge algorithms/models to analyze diverse sources of data to achieve targeted outcomes; I.e., be up to date on data science research (papers and libraries); be able to build and evaluate models yourself
  • Conduct analysis and turn insights into actionable changes for predictive models or policies; have experience identifying and prioritizing the business impact
  • Recommend ongoing improvements / tuning to methods and algorithms currently in use/production
  • Deliver informative and effective findings, results and recommendations from statistical analysis to stakeholders, both technical and non-technical audiences
  • Effectively mentor non-statistical programming peers about statistical programming practices.
  • MS in Statistics, Economics, Finance, Survey Research or other related quantitative field
  • Strong understanding of Computer Science fundamentals
  • 4+ years Statistics/data modeling in an applied context
  • Proven track record of building new models and improving existing models
  • Strong attention to detail; excellent communication and project management skills
  • Thorough understanding of statistical modeling techniques
  • Advanced Python or R; we are a primarily-Python shop
  • Exploratory data analysis and visualization
  • Experience with marketing mix modeling, digital attribution modeling, multivariate regression, time-series modeling, Bayesian statistics, segmentation modeling, machine learning, data mining, simulation, optimization, forecasting
  • Have a portfolio (e.g., website, github, paper references, etc.) of papers, visualizations, or software
  • Agile, Scrum experience
  • Salesforce
  • Strong SQL; we primarily use MySQL
  • Big data: e.g., competence with Spark, Redshift or Snowflake

Desirable Experience:
  • Profession experience at a financial services organization
  • Econometric modeling, traditional modeling techniques (regression, tree-based models), deep learning

Position Application Instructions:
Interested candidates should send a resume to:

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