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Equifax, Inc.

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Sr. Director (Principal Data Scientist) (Finance)



SUMMARY OF ROLE HERE (REMOVE THIS INSTRUCTION)
  • What you'll do
    • Utilize subject matter expertise of data structures, analytics, algorithms/models, and strong computer science fundamentals to lead data preparation, analytics, and development of deployable solutions across multiple projects
    • Collect, analyze and interpret large data assets to define and build multiple innovative solution components leveraging business and technical expertise. Lead the analytical strategy on critical technical capabilities
    • Contribute to evaluation of new data sources, provide recommendations on value of data sources, and design code to improve the productivity of Equifax, enhance and update code where needed.
    • Perform as lead technical data scientist for multiple technical and business domains, collaborating with other teams to develop predictive models, risk assessments, fraud detection, recommendation engines, etc. encouraging enhanced solutions and asking questions
    • Able to analyze and prepare complex and new data sources and incorporate them into analytical solutions.
    • Package, summarize, visualize and perform storytelling on analytical findings and results for management and business users
    • Communicate results to senior management and external stakeholders, able to communicate the strategic impact of the work
    • Evaluate the technical work of experienced data scientists guiding them on deliverable quality and accuracy
    • Serve as SME consultant for COE / Business Unit / Regions, share best practices globally
  • Key Skills:
  • Artificial Intelligence - Identify, utilize, and develop artificial intelligence differentiators which will improve process efficiency and effectiveness, products, and client solutions.
  • Collaboration - Work collaboratively across different projects, communicating technical details to technical and non-technical external stakeholders and senior management. Manage challenging projects and own priorities within and across teams.
  • Commercial Acumen - Act as an SME on multiple products and related market segments and to translate complex commercial problems into technical solutions and vice versa
  • Decision Modeling - Use advanced statistical concepts to develop and review stress tested deployable machine learning algorithms (Logistic Regression, Xgboost, Neural Networks, etc.) along with understanding and anticipating associated performance and business implications.
  • Leadership and Teamwork - Foster a collaborative and productive team environment, coaching others to develop technical and non - technical skills and lead medium sized data science projects.
  • Problem Solving - Identify and flag complex problems in data, models, processes and projects and guide others in the identification and delivery of the most applicable resolutions to business problems.
  • Statistical Programming - Design efficient reusable code and solutions that improve overall productivity and drive technical best practice of the team or department.
  • What experience you need

    • BS degree in a STEM major or equivalent discipline; Master's Degree strongly preferred
    • 7-10 years of experience in a related role, with experience demonstrating leadership capabilities
    • Proven track record of designing and developing predictive models in real-world applications
    • Experience with model performance evaluation and predictive model optimization for accuracy and efficiency
    • Cloud certification strongly preferred
    • Additional role-based certifications may be required depending upon region/BU requirements
  • What could set you apart
    • Prior 3+ years direct management experience.
    • Credit risk and Fraud Risk model development experience
    • Financial vertical experience
    • GenAI driven solutioning
    • Extensive experience on various credit and fraud risk models
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