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Hybrid Data Scientist II Data Scientist II

Infraveo Technologies  ·  nan, · Hybrid

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About the job

We are seeking a Data Scientist II to join our team.

Key Responsibilities

  • Work effectively with internal stakeholders to meet the data needs of the business, translating business needs into analytical requirements.
  • Manage multiple projects simultaneously and prioritize them appropriately.
  • Demonstrate a proactive work style and creative problem-solving skills, while handling multiple projects and maintaining a strong work ethic.
  • Pay close attention to detail, quality, and follow-through with a commitment to continuous improvement and the elimination of performance variability.
  • Conduct statistical analyses, build predictive models, and support decision engine configuration.
  • Present information using data visualization techniques.
  • Document all processes and research thoroughly.Presents information using data visualization techniques.

Requirements

  • Excellent verbal and written communication skills.Proficient with Microsoft Office Suite or related software.
  • Excellent organizational skills and attention to detail.
  • Excellent time management skills with a proven ability to meet deadlines.
  • Strong analytical and problem-solving skills
  • Ability to function well in a high-paced and at times stressful environment.
  • Undergraduate degree in Applied Statistics, Predictive Analytics, or similar.
  • Traditional modeling experience using Logistic and Linear Regression.
  • Ability to discover insights from disparate data sources.
  • Machine learning experience.
  • 5+ years of Consumer Finance analytical experience.
  • Python or R coding experience.
  • SQL coding experience.
  • Data ingestion and cleansing experience.
  • Credit Bureau data experience.
  • Decision Engine management experience.
  • Auto Finance experience.

Benefits

  • Work Location: Remote
  • 5 days working


Desired Skills and Experience

Machine Learning, Statistical Analysis, Python Programming, Data Visualization, Big Data, Predictive Modeling, Data Mining, Deep Learning

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