Data Scientist

Employer: McGuireWoods


McGuireWoods delivers excellent results for our clients, and our Data Analytics team is an essential part of the equation. The Data Scientist is positioned to work directly on critical firm initiatives that will deliver on the firm's strategic charge to develop and refine innovative ways to serve clients and build our brand. This role will work with stakeholders across the organization to deliver analytically-driven solutions to our clients' and the firm's challenges. This is a great opportunity to join a growing team and make an impact immediately. The selected candidate can sit in one of the following McGuireWoods locations: Richmond, VA, Charlottesville, VA, Washington, DC, Tysons, VA.

Responsibilities -

  • Work with attorneys and professional staff to identify business opportunities to use data to drive strategic decision-making, and build analytical solutions for our clients and the firm

  • Work as a data science consultant with clients and attorneys on legal matters

  • Analyze client and firm data, using statistical techniques including machine learning and natural language processing to develop/validate/improve/implement predictive models to optimize outcomes and reduce unpredictability

  • Present complex analyses to a wide range of audiences in a consumable manner

  • Work collaboratively on the McGuireWoods Data Analytics team, and respond quickly to time-sensitive requests

Qualifications -

  • 3+ years of analytical experience

  • Requires a Bachelor's Degree, preferred but not required in a technical or quantitative field

  • Experience with open-source languages for data analysis, and using SQL with relational databases

  • Experience with data presentation and storytelling via tools like Power BI or Tableau

  • Experience working on Agile teams and with Git version control

  • Understanding of basic statistical concepts (hypothesis testing, regression, Normal distribution, etc.)

  • Excellent written and verbal communication skills with the ability to explain technical data analysis approach and results to business stakeholders

  • Data engineering experience in scripting and scheduling ETL workflows a plus

  • Experience with cloud technology (Azure, AWS, or GCP) a plus

We're looking for self-starters who can think outside the box, work collaboratively with stakeholders, and deliver results!