Mid-Level Data Scientist
Information Technology | Washington, DC | Full Time
Demonstrated experience analyzing data using SQL, Excel, and a programming language (either Python or R).
Demonstrated experience using Unix or Linux platforms to maintain work products.
Demonstrated attention to detail, critical thinking, and ability to find simple, interpretable solutions to complex data problems.
Demonstrated experience writing queries as part of data processing code that is selfdocumenting and clean.
Demonstrated experience in developing analytics solutions that are scalable and repeatable.
Demonstrated experience using Github, and Git.
Experience working with subject matter experts in a regulatory environment, including attorneys, researchers, and/or economists. This requires translation of technical analysis and results for non-technical audiences. Inclusive of at least one of the following:
(1) Experience providing technical expertise for attorneys conducting work on topics such as: litigation, depositions, witness/expert witness preparation, crossexaminations; experience using and extracting information from legal review platforms, with quantitative analysis of data from foreign sources, reverse engineering of data formats, and/or calculating damages.
OR (2) Experience providing technical expertise for non-technical researchers/subject matter experts, using multiple advanced analytical and statistical techniques such as: natural language processing, time-series modeling, predictive modeling, valuation of options and derivatives, sampling, sample size calculations, hypothesis testing, and/or A/B testing.
Experience working closely with a variety of teams to identify, diagnose, troubleshoot, and resolve technical, strategic and/or analytical issues.
Experience performing statistical analysis and manipulation, using programming languages/software such as SQL (window functions, common table expressions, inner/outer joins, materialized views), Excel (lookup, index/matching, offset function, pivot tables), Python (including Pandas and Numpy libraries), R (including tidyverse), R-Shiny, and/or Spark.
Experience providing training on a variety of development and data methodologies and/or tools to include new technologies and solutions that could help the Data Science Team and the Bureau at large.
Software or data engineering experience.
PhD or degree in a math, hard science or quantitative social science field.
Experience working in an AWS cloud environment.
Prior Government experience in order to expedite the onboarding clearance process. Familiarity with the eQIP system and SF86 forms helpful.