Civis Analytics: Data Scientist – Engineering (Senior and Junior roles)
Founded by a team from Obama 2012, we are helping companies, non-profits, and campaigns leverage their data. Integrate, scale, and optimize our team data science methods, techniques, and best practices to run on very large datasets at high speeds.
Location: Chicago, IL
Apply online at http://civisanalytics.com/careers.
Who We Are
Our Company is a Chicago-based Big Data analytics firm born in a large windowless back room of President Obama's 2012 re-election campaign. We called it "The Cave."
Beginning with the campaign, our mission as a team has been clear: help great organizations use their Big Data to solve their biggest problems. We are now applying our analytical expertise, specialized software, and innovative technological approach to help companies, non-profits, and campaigns leverage their data to develop smarter strategies, make better decisions, and build stronger, data-driven organizations. In the year since our company's founding, we have helped solve problems as diverse as enrolling individuals for health insurance, optimizing TV ad purchases to reach more targets, and pinpointing individuals who want to sign up for a clean energy utility company.
We are not a group of spreadsheet management consultants; we are an inventive team of the best statisticians, scientists, engineers, and technologists in our fields building things that have never been built before. And we're looking to add to our team.
Why should you join our team?
We are already solving some of the world's most demanding and complex problems with Big Data - working with organizations to analyze and understand their individual level intelligence to improve outcomes and implement organizational change. We work on teams with diverse skill sets to apply and invent new data science techniques, putting us at the forefront of innovation in our field as we solve problems that have never been solved before.
We are smart, fun, and a little bit weird. Does this sound like you?
The Research and Development team is responsible for developing the fundamental data science methods, techniques, and best practices that power the mission of our company. Our diverse work includes predictive analytics, algorithm development, experimental design, visualization, and survey research. As a Data Scientist on our Chicago-based Research and Development team, you will work closely and collaboratively with analysts and engineers to develop and operationalize the techniques that quantify and solve big, meaningful problems. Our team dives deeply into big problems and works in a variety of areas.
With a specialization in engineering, this Data Scientist role will tackle the challenging computational and programming problems that are critical for the creation and application of new data science methods to Big Data. In this position, you will integrate, scale, and optimize our team's data science methods, techniques, and best practices to run on very large datasets at high speeds. You will also play a critical role in the development of completed data science research into client-facing tools - ensuring that what we build is automated, scalable, robust, and getting used to solve real business problems.
We are looking for individuals from a diversity of backgrounds with demonstrated quantitative and problem-solving skills. We value creativity, hard work, and on-the-job-excellence and offer competitive compensation and benefits packages. In compliance with federal law, all persons hired will be required to verify identity and eligibility to work in the United States.
- Bachelor's degree in a technical field, such as statistics, machine learning, physics, engineering, or computer science
- Experience using applied statistics or machine learning in a professional or other intensive problem-solving environment
- Experience with Python, and in particular, the Python scientific stack (NumPy, SciPy, scikit-learn, pandas)
- Experience with Linux and shell scripting
- Experience with github
- Experience identifying and correcting for problems in imperfect data
- An ability and eagerness to constantly learn and teach others
- PhD in a technical field, such as statistics, machine learning, physics, engineering, or computer science, or a Master's degree and outstanding work experience.
- Strong experience in software engineering and maintaining a code base
- Ability to expand upon modern statistical learning methods
- Significant work experience in statistical modeling or machine learning
- Expertise in the Python scientific stack (NumPy, SciPy, scikit-learn, pandas)
- Expertise in programming with Python
- Familiarity with Go (golang)
- Experience with SQL databases
- Experience with Map Reduce (AWS, EMR, Hadoop, Hive, Pig, Spark)
- Expert ability to identify and adapt to imperfect data
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