Remote Data Scientist

Summary

Join ShyftLabs as a Data Scientist to drive performance improvement and cost efficiency in our product through data analysis, simulation, experimentation, and causal inference. We're looking for someone with a Master's degree in a quantitative discipline or equivalent, 5+ years of experience, and strong knowledge in statistics, machine learning, and programming.

Requirements

• Master's degree in a quantitative discipline or equivalent
• 5+ years minimum of relevant professional experience
• Distinctive problem-solving skills, good at articulating product questions, pulling data from large datasets and using statistics to arrive at a recommendation
• Excellent verbal and written communication skills, with ability to present information and analysis results effectively
• Ability to build positive relationships within ShyftLabs and with our stakeholders, and work effectively with cross-functional partners in a global company
• Strong knowledge and experience in experimental design, hypothesis testing, and various statistical analysis techniques such as regression or linear models
• Deep understanding of ML algorithms (i.e. deep learning, random forest, gradient boosted trees, k-means clustering, etc.) and its development, validation, and evaluation
• Experience with Python, R or other scripting language, and database language (e.g. SQL) or data manipulation (e.g. Pandas)

Responsibilities

• Analyze a large dataset with queries and scripts, extracting valuable signals out of noise, and producing actionable insights into how we could complete and improve a complex ML and bidding system
• Validate and quantify the efficiency and performance gain from hypotheses through rigorous simulation and modelling
• Develop a robust experiment design and metric framework, and provide reliable and unbiased insights for product and business decision making

Benefits

• Competitive salary
• Strong healthcare insurance and benefits package
• Fully remote work option within the United States
• Extensive learning and development resources