Apply your expertise in quantitative analysis, data visualization and artificial intelligence to find insights and patterns that can be used to automate manual tasks. Get an opportunity to work on a new product, this product leverages AI to automate manual, costly lender workflows.

Responsibilities: 

• Develop data science products that perform automated processes/quality checks on a wide array of closing documents
• Work with other members of Data Science team on computer vision and NLP tasks
• Build and maintain multiple production services, implementing bug fixes and code quality improvements
• Build processes that enable our less technically skilled Data Science operations team to own mature product repos
• Work cross-functionally with Product, Engineering, Customer Success to coordinate efforts to create and improve Closing Quality Control Products overall

The ideal candidate is someone who relishes pouring over messy data to find patterns and train machines to do so with high accuracy and recall. You have have 2+ years of Data Science experience, most of which were focused on product oriented work. You have an expert level understanding of Python, SQL and cloud technologies like AWS. You have a proficient understanding of advanced machine learning techniques and we’ll give you bonus points for experience in Computer Vision, NLP and or Deep Learning. You’re a data wrangler with a passion for learning new technologies and collaborating with your colleagues while being curious and asking questions that result in actionable insights. You are a self-starter and seek out interesting problems to dig into until you understand it’s nuances and uncover solutions. Lastly, you are empathetic, have strong verbal communication skills and can talk to both engineers and customers alike.

If you are located in NY, CA, WA or MA, the salary range for this role is $143,400.00 - $194,000.00. For all other locations, the range is $125,500.00 - $169,700.00. As a new hire, your starting salary will likely be between the 25th percentile and the midpoint of the range; however, all offers are based on the successful candidate’s experience and qualifications.