Senior Data Scientist

Ex Parte, Inc; Bethesda (MD); On-site; USD 120,000 - 150,000; Full time

Job summary

Ex Parte, Inc. is seeking a Senior Data Engineer in Bethesda, Maryland, to drive AI and machine learning initiatives. The ideal candidate will thrive in a fast-paced environment and possess 5+ years of experience in data science, particularly in solving enterprise-specific problems.

This role emphasizes building effective models and working collaboratively with engineering teams to deliver impactful solutions. Preferred qualifications include a strong background in SQL, Python, and familiarity with modern data science tools.

Qualifications

• 5+ years of applied data science experience with a focus on enterprise challenges.
• Experience in managing and mentoring teams for technical projects.
• Knowledge of machine learning techniques and data analysis tools.

Responsibilities

• Drive the technical roadmap for risk monitoring.
• Produce high-performing data science models.
• Onboard new talent and ensure feedback loops between teams.

Skills

Machine Learning

Data Science

Team Leadership

Statistical Analysis

Communication Skills

Python

Education

Bachelor's degree in Statistics, Data Science, or AI

Tools

SQL

Python

Azure ML

Databricks

TensorFlow

Job description

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 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.

Job Description

• Drive technical roadmap to extend risk monitoring across identified threat surfaces.
• 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.

Qualifications

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).

Additional Information

All your information will be kept confidential according to EEO guidelines.