Spreetail

Principal Data Scientist

Job Description

We are looking for a Principal Data & Applied Scientist to lead our causal AI decision engine, working across every area of our company, and driving the applied mathematical frameworks and experimentation designs to achieve a best-in-class system. This role reports to our VP of Decision Science and will work with a talented team of executives and experts—including direct-to-CEO visibility and influence over the entire company's roadmap. This team and leader are responsible for the largest learning models at Spreetail and take pride in being the first to solve many practical decision science challenges at scale. You will be looked to as the most senior data scientist in the company and expected to inform and improve our highest priority initiatives that data and decision science can shape.


This position is 100% remote in select states:
  • In order to qualify for remote work, candidates need to reside or be willing to move to Alaska, Arizona, Colorado, Florida, Georgia, Hawaii, Illinois, Indiana, Kentucky, Massachusetts, Nebraska, Nevada, New Hampshire, New Jersey, North Dakota, Pennsylvania, South Dakota, Tennessee, Texas, Utah, Washington, or Wyoming.

    • How you will achieve success:
  • Build best-in-class data models and algorithms that drive business actions at a massive scale.
  • Your models are flexible and responsive to fast-changing variables or a significant influx or departure of variables from the model.
  • Your models are trained, tested, and deployed with quality and efficiency.
  • You can break down major initiatives and insights needs into smaller components and tasks.
  • The systems you build are documented and easily explained to your business and Technology stakeholders.
  • You embody the Science & Technology Principles and use them to guide decisions.
  • As a premier data expert in our company, you create an environment of knowledge sharing and growth, placing a high priority on leading and developing others.

    • What experiences will help you in this role:
  • Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical, Computer Engineering, or related field AND 6+ years of related experience (e.g., statistics, predictive analytics, research)
  • OR master's degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or a related field AND 4+ years of related experience (e.g., statistics, predictive analytics, research)
  • OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years of related experience (e.g., statistics, predictive analytics, research)
  • OR equivalent experience.
  • Advanced-to-expert level skills in Python for statistical programming.
  • Demonstrated excellence in a data science/modeling role.
  • Hands-on experience building and deploying end-to-end causal inference models at scale.
  • Advanced-to-expert level SQL extract (SELECT statements) skills required; expertise preferred
  • Advanced-to-expert level experience with “big data” storage and processing technologies (Hadoop, Apache Spark, Azure Synapse, Snowflake, etc.) required.

    • Preferred qualifications:
  • PhD in Mathematics, Statistics, Machine Learning, or a related quantitative field
  • Experience in data applications using large-scale distributed systems (e.g. EMR, Spark, Elasticsearch, Hadoop, Pig, Hive) and AWS platforms such as S3, Glue, Athena, and Sagemaker.
  • Previously held a technical leadership role for several complete large-scale initiatives

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