You will be joining a best-in-class team on a trajectory of tremendous growth. We are a Series-B start-up, backed by top tier investors Canapi Ventures, FinVC Capital, and TTV Capital and we serve some of the largest names across various industries such as Intuit, Square, Affirm, Mission Lane, Petal, and others.

We are pioneering the behavioral analytics space, providing a new standard for collecting, translating and actioning on the real-time behaviors of digital interactions. Through a body of patented technology leveraging over a decade of scientific research and discovery in Human-Computer Interaction (HCI) to measure both customer Intent and Experience. For companies, this real-time behavioral data is used during the digital onboarding process to segment genuine from fraudulent customers, enabling them to maximize conversion, reduce false positives and stop sophisticated fraud.

Founded by 2 world-renowned PhDs, and led by a team of seasoned executives, we continue to make strategic key additions to our team to expand our product offerings and enter new verticals.

We have a large and unique data set with a unique set of challenges. It has tremendous potential. We are looking for an experienced data scientist to join our team, and take our modeling and ML to the next level.

JOB RESPONSIBILITIES:

• Research and develop ML learning models and technology to power the behavior-as-a-service platform
• Collaborate with engineering and other teams to deploy models into production.

REQUIRED QUALIFICATIONS:

• 5 years experience delivering data science projects analyzing and modeling large scale-multi dimensional data, preferably in an industry setting
• Proven knowledge in model evaluation, tuning and performance, operationalization and scalability of scientific techniques and establishing decision strategies
• Hands on experience developing supervised and unsupervised machine learning algorithms (regression, decision trees/random forest, neural networks, feature selection/reduction, clustering, etc.)
• Fluency in Python, especially the data scientific stack (Jupyter/Pandas/sci-kit-learn)
• Working knowledge of relational databases (e.g. PostgreSQL), experience with Snowflake and/or Looker is a plus
• Experience with cloud computing platforms (AWS, Azure, etc.)
• Outstanding communication skills (verbal, written and remote)

PREFERRED QUALIFICATIONS:

• You have worked in a fraud data team at a financial institution.