- Drive technical roadmap to extend risk monitoring across identified threat surfaces.
Develop/experiment/ship state-of-the-art prediction models
Use excellent data science practices to iteratively produce high performing models
Create immediate impact through sound and practical deliveries of risk monitors
Work with engineering colleagues to convey findings through data visualizations
Measure, tune and refine existing algorithms to incrementally improve performance
Analyze new and existing data after extracting. transforming and combining it in novel ways
Convey needs to engineering and operations teams to ensure healthy feedback loops
Attract and onboard new talent while preserving and enhancing existing culture
Build strong partnerships and collaborate with other teams across the enterprise
Demonstrate sense ownership and personal accountability for your team's work
Basic Qualifications:
5+ years applied data science experience, including 3 years of advanced analytics experience focused on enterprise-specific problem solving
2+ years management, mentoring, or other closely related team or people leadership experience
Experience in machine learning (supervised, semi-supervised or unsupervised learning)
Strong communication, delivery management, and leadership skills
Preferred Qualifications
A bachelor’s degree, MSc or Ph.D. in Statistics, Data Science, Artificial Intelligence, or equivalent alternative education or experience
Applied experience with SQL, also Python or R or Scala, and modern data science tools/packages e.g. PyTorch, Transformers, TensorFlow, scikit-learn
Applied experience with Databricks and/or Azure ML
Strong coding abilities in one or more scripting languages like Python or SQL
Understanding of compliance, security, and risk domains along with associated patterns and data elements
Understanding of product and services activation, use, and transaction models and data
Understanding of statistical analysis and machine learning tools and practices
Understanding of Cloud-centric data processing and visualization approaches including SQL and NoSQL databases with exposure to Azure SQL, Azure Cosmos DB, Data Factory, Synapse, Azure Data Lake, etc
Familiarity with Agile software delivery including application lifecycle mgmt (SAFe, Azure DevOps/VSTS, Git)
All your information will be kept confidential according to EEO guidelines.
Ex Parte provides our customers with the data and insight to make smart and informed decisions on the most important legal issues facing their organizations.
We are is looking for talented, enthusiastic senior data engineers who share our passion for big data, AI, and machine learning and are excited by seemingly-impossible challenges. As an early employee, you must be amazingly entrepreneurial and thrive in a fast-paced environment where the solutions aren’t predefined.
Every year, corporations spend more than $250B on litigation in the United States alone. And yet, critical decisions such as whether to litigate or settle, or where to file suit or which attorney to hire, are all made the same way they were 100 years ago.
We are applying artificial intelligence, machine learning, and natural language processing to provide our customers with the insight they need to make highly informed decisions and gain a winning advantage. Think of it like Moneyball, but for a market more than 20x the size of Major League Baseball.
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