Axiom is a recognized leader in the business of law, and defined the “alternative legal services” category over 20 years ago.  While not a law firm, Axiom would rank among the top 10 big law firms by number of lawyers employed.

Axiom manages a diverse global network of legal professionals that are matched to engagements with Axiom’s prestigious clients using a bespoke technology platform.  While Axiom has made progress to automate this matchmaking process using machine learning, the vast majority of matches are still made manually by Axiom staff.

Axiom is ready to transition from manual to automated matchmaking by pioneering technologies within the machine learning space. Using NLP and other data extraction, Axiom seeks to build out the capability to identify the best talent for roles at the right time. Pulling information out of the vast database of Talent and Client preferences, Axiom believes it can provide best in class experiences to the broad Axiom Talent Network.

To enable this transformation, Axiom’s Research & Development department is adding its first data science team.  This is your opportunity to join at the beginning of Axiom’s data science journey and chart the course of Axiom’s future.

The Role

The data science function within Axiom R&D is new, but with big eyes. A dedicated team focused on solving the deeper questions, the initial data science pod will be comprised of a dedicated Technical Product Manager, Data Engineer, and Data Research Scientist (this role).

Axiom is looking for a Research Scientist to define and build solutions that discover new and innovative ways to utilize the data within Axiom’s reach.

Our team’s mission is to constantly challenge the status quo and drive innovation to improve our Client, Talent, and Internal user’s experiences. This role requires an expert in the areas of machine learning and statistics who can adapt theoretical models to an applied environment. The ideal candidate will have experience with models for natural language processing tasks.

A successful candidate will have a passion for clarity, be a self-starter comfortable with ambiguity, have strong attention to detail, be able to work in a fast-paced and entrepreneurial environment and be driven by a desire to innovate. Given the complex nature of the questions we are working on, the ideal candidate will be relentlessly curious and be able to/be interested in having the business conversations underlying the data.

Specifically, this role will:

• Design and build ML solutions that capture business and customer insights from various sources and help drive business outcomes
• Collaborate with engineers and product managers to design and implement ML solutions
• Continuously interrogate, improve, and experiment with new and existing ML solutions at Axiom
• Provide technical and scientific guidance to your peers and team members
• Publish and present your work at internal and external scientific venues in the fields of ML

Required Qualifications

• Bachelor’s Degree or equivalent experience
• 3+ years of demonstrated proficiency with data querying using SQL
• 3+ years of demonstrated data modeling techniques in R or Python
• 3+ years of demonstrated proficiency deploying reporting and analytics representing modeling outputs
• 2+ years of applied research experience
• 2+ years of experience defining research and development practices in an applied environment
• 2+ years of experience reviewing research papers, algorithms, and code
• Strong relationship-building and stakeholder-management skills
• High technical acumen and ability to communicate effectively with a variety of technical stakeholders
• Self-starter with strong sense of ownership, drive for results, and problem-solving skills

Preferred Qualifications

• Masters or PhD in computer science, machine learning, mathematics, statistics, or another quantitative field
• Experience working with AWS big data processing technologies (S3, Sagemaker, Redshift, EMR, Spark)
• Experience in data modeling, ETL development, and data warehousing
• Familiarity with NLP and statistical models
• At least one record of publication in machine learning
• Knowledge of software engineering best practices across the development lifecycle, including agile methodologies, coding standards, code review, source management, build processes, testing, and operations
• Familiarity with Jira, Confluence, and gitlab

Axiom is an equal opportunity employer and committed to a diverse workforce.