Applied Data Scientist (Contract)

Civis Analytics

About The Position

The Applied Data Science (ADS) team is the consultancy arm of Civis Analytics, working closely with clients to help solve their toughest challenges with data science. An Applied Data Scientist is responsible for the end-to-end execution of new client engagements utilizing data science, which includes unifying large 1st- and 3rd-party datasets and building predictive models, deriving clear, actionable, and timely insights from analyses, creating client-ready materials and solutions for stakeholders of varying technical experience or familiarity with methods, and working with cross-functional teams of data scientists and software engineers where necessary to create and implement solutions. Other job responsibilities include creatively identifying opportunities in the solution delivery process for scalable applications, and collaborating with other teams to further construct these tools, and maintaining a continuous and independent education of cutting-edge statistical techniques and programming languages.

Requirements

Bachelor’s degree in an analytical subject (statistics, math, economics, physics, engineering, business, political or social science, computer science, etc.)
Proven affinity for and experience working with large or messy data sets using SQL
Experience with statistical programming languages (R, Python, etc.) and proven ability to work pragmatically with statistical concepts
Experience with presentation or data visualization software, such as Powerpoint, Tableau, Shiny, Streamlit, etc.
Excellent interpersonal and communication skills
US work authorization
Candidates must currently live in the following states: DC, Florida, Illinois, Maryland, Michigan, North Carolina, New York, Pennsylvania, Texas, Vermont. Virginia

Nice To Haves

Practical understanding of and experience with predictive analytics, machine learning, and/or causal inference
Experience with marketing modeling and analytics (e.g., LTV, Lift)
Familiarity with software development tools and practices (Git, code review, etc.)
Familiarity with dbt
Familiarity with AI tools and LLMs (Claude, ChatGPT, Gemini, etc.)

Responsibilities

Unifying large 1st- and 3rd-party datasets and building predictive models
Deriving clear, actionable, and timely insights from analyses
Creating client-ready materials and solutions for stakeholders of varying technical experience or familiarity with methods
Working with cross-functional teams of data scientists and software engineers where necessary to create and implement solutions
Creatively identifying opportunities in the solution delivery process for scalable applications, and collaborating with other teams to further construct these tools
Maintaining a continuous and independent education of cutting-edge statistical techniques and programming languages