Data Scientist
As a Data Scientist, you will help Paylocity discover the information hidden in vast amounts of data, to help our customers make smarter human capital decisions that drive organizational success. Your primary focus will be to apply knowledge of statistics, machine learning, programming, data modeling, simulation, and advanced mathematics to recognize patterns, identify opportunities, pose business questions, and make valuable discoveries leading to prototype development and product improvement.
Are you the teammate we are looking for?
Who you are:
- Enthusiastic about advanced analytics and how predictive insights lead to a superior customer experience
- Invested in staying current in data science by applying new technologies and practices
- Able to work in a collaborative environment with a desire to share your ideas
- Able to work independently on modules and complete tasks with high quality, but unafraid to seek out suggestions from other team members
- Excited to work on cutting-edge technology!
During the first three months at Paylocity, you will:
- Select features, build and optimize classifiers using machine learning techniques such as random forests, xgboost, TensorFlow, linear regression, time series methods
- Collaborate with Product Owners, Sales Leaders, Enterprise Architects and other executives to translate complex human capital management challenges into data science projects
- Extend company’s data with third party sources of information when needed
- Enhance data collection procedures to include information that is relevant for building analytic systems
- Leverage cutting edge big data technologies on AWS and Microsoft Azure
- Conduct ad-hoc analysis and present results in a clear manner
- Create automated anomaly detection systems and tracking of its performance
- Work closely with full stack .net engineers in an agile product development environment
What you bring:
Demonstrated ability to leverage data science to drive business results. Some ways previous successful candidates have demonstrated this are:
- 3-6 years of data science success at other software companies
- Recognized success for data science skills via academic awards, scholarships or corporate recognition programs (Employee of the Year, etc.)
Experience in writing production grade machine learning models in Python. Some ways previous successful candidates have demonstrated this are:
- A portfolio of publicly available data science projects that resulted in a fully functioning piece of software
- Strong academic publication or speaking record in organizations such as ICML, NeurIPS, JML, KDD, and INFORMS
- History of strong performance in Kaggle competitions
- Experience with cloud infrastructure on AWS or Azure
Skilled at translating business problems into data science problems and communicating the results to non-technical audiences. Some ways previous successful candidates have demonstrated this are:
- A resume or cover letter outlining previous experience leveraging data science across many domains
- A professional or academic track record of teaching mathematical or data science concepts to non-traditional audiences
Experience or interest for leveraging technology and data to empower employees. Some ways previous successful candidates have demonstrated this are:
- Professional or academic experience in HR, social science or psychology
Advanced degree (Masters or Phd) preferred in computer science, industrial engineering, statistics, industrial organizational psychology, neurology, public policy, linguistics or other quantitative field preferred. Bachelor’s degree required.