Senior Applied Data Scientist

We're looking for a highly skilled and experienced data scientist to join our team as a Principal Data & Applied Scientist. As a key member of our data science team, you will play a critical role in driving our causal AI decision engine and developing mathematical frameworks and experimentation designs to achieve a best-in-class system.

This role requires a strong background in data science and machine learning, as well as excellent communication and collaboration skills. You will work closely with our VP of Decision Science and a talented team of executives and experts, including direct-to-CEO visibility and influence over the entire company's roadmap.

This is a 100% remote opportunity in select states: 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. To qualify for remote work, candidates must reside or be willing to move to these locations.

Key Responsibilities

• Develop best-in-class data models and algorithms that drive business actions at a massive scale.
• Build and deploy end-to-end causal inference models at scale.
• Collaborate with cross-functional teams to drive business outcomes.
• Stay up-to-date with the latest advancements in data science and machine learning.
• Communicate complex ideas effectively to both technical and non-technical stakeholders.

Requirements

• 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.