Associate Data Scientist
CentralSquare Technologies | Development | Greensboro, NC
The Central Square Labs team is seeking an associate data scientist to join the team in building new, innovative solutions for public safety and administration. You will work with a team of data scientists, engineers, UI/UX designers, and product managers to create cloud-based applications that use data analysis and machine learning to support new capabilities across the Central Square product line. You understand basic machine learning ideas and want to advance your skills while you contribute to a growing team creating solutions that are both scalable and supportable. Your entrepreneurial energy and desire to have an impact in society make you challenge the status quo and strive to learn how to apply new tools and approaches to solve difficult problems.
About Central Square Labs
The innovation Lab at Central Square is a new team tasked with prototyping and scaling new, emerging solutions to support the broader Central Square mission of improving communities through our public safety and administration solutions. As a new team, we are ramping up our engineering efforts with a focus on creating cloud-based data analysis pipelines that use machine learning to improve the efficiency and effectiveness of government agencies. For instance: How can machine learning make police patrols more efficient and equitable? How do we craft ML models that are not only accurate but also fair and transparent? How do we deliver ML services to other teams in a supportable and scalable manner? If these questions speak to you, then the Labs team is the right environment in which to answer them.
What You’ll Do
- Craft classification and regression predictive models using machine learning techniques
- Build modeling pipeline components using Python
- Support other data scientists in data examination and cleaning
- Receive feedback on your data science code through code reviews
- Collaborate with engineers to support feature engineering and production roll-outs
You Should Have
- Understanding of common ML techniques (k-NN, random forests, boosting, penalized regression, deep learning) and best practices (cross validation, hyperparameter tuning)
- Basic experience with ML tools (Tensorflow, Pytorch, or Sci-kit Learn)
- Basic proficiency in processing tabular data (e.g. Pandas / R / Spark dataframes)
- Excellent verbal and written communication skills
- Basic proficiency with Python
You Get Extra Points For
- Degrees relevant to Computer Science, Mathematics, Statistics and Data Science
- Experience with SQL
- Experience with data visualization tools (D3, Plotly, ggplot2)
- Experience using big data analytics platforms such as Dask or Apache Spark
- Experience with additional programming languages such as Scala or R.
- Experience with Agile methodologies (e.g. Scrum, backlog grooming, sprint planning)