Data Analytics Scientist

8 - 10 years experience  •  Legal Services

Salary depends on experience
Posted on 11/27/17
Richmond, VA
8 - 10 years experience
Legal Services
Salary depends on experience
Posted on 11/27/17


  • Collaborate with lawyers and staff to identify opportunities to solve problems and gain insight to client and other firm issues. This role directs data analytics for proper and efficient utilization of data to bring understanding to complex situations.
  • Assist other IT departments with advanced functions of software tools, i.e. combining data files, using complex Excel functions, etc.
  • Develop data preparation, sample design, and identify appropriate analytic and statistical methodology, and document process and results.
  • Analyze and model structured data using advanced statistical methods, and implement software/algorithms to perform analysis.
  • Perform machine learning, natural language, and statistical analysis methods as appropriate, such as classification, collaborative filtering, association rules, sentiment analysis, topic-modeling, time-series analysis.
  • Perform explanatory data analysis, generate and test working hypotheses, prepare and analyze historical data, identify patterns and interpret results, and be able to explain to all levels of stakeholders.


  • At least 7-10 years of data analytics experience in a professional services firm or similar environment with proven experience using large amounts of data to solve analytical problems.
  • Business acumen with excellent statistical and analytical skills, problem solving skills, and communication skills.
  • Experience with R programming language. (Python or SAS would be a plus as well).
  • Experience with the application of advanced data analytics, including data and text mining, predictive modeling, risk-based optimization and advanced operations research, and data visualization.
  • Working knowledge of databases and SQL.
  • Requires a Bachelor’s Degree in a technical or quantitative field; Master or MBA degreepreferred.
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