Machine Learning Engineer

Key Responsibilities: Machine Learning Engineer, Data Science About the Team Data is at the core of our company's strategy. It drives ourselves and our customers to the highest levels of success. We use it for everything from customer health scores and revenue dashboards, to operational metrics of our AWS infrastructure, to helping increase product engagement and user productivity through natural language understanding, to predictive analytics and causal inference via experimentation. As our customer base continues to grow, we are looking towards new ways of leveraging our data to deeper understand our customers’ needs and deliver new products and features to help continuously improve their customer engagement workflows. The mission of the Data Science team is to enable continuous optimization by reconstructing customer engagement workflows from data, developing metrics to measure success and efficiency, and providing insights and tools to support execution and optimization of these workflows. As a member of the team, you will work with other Data Scientists, Machine Learning Engineers, and Application Engineers to define and implement our strategy for delivering on this mission. Your Daily Adventures Will Include: • Designing, developing, and deploying machine learning and recommendation applications to production. • Designing and implementing state-of-the-art models for forecasting, causal inference, and optimization. • Building large-scale simulation systems to help leaders conduct what-if analysis. • Working with internal and external customers to understand their pain points and brainstorm solutions. • Ensuring the data that feeds into our machine learning models is reliable, accurate, and punctual. • Working alongside experienced engineering, design, and product teams to help deliver new customer-facing features and products. • Serving as an expert in areas like forecasting, causal inference, explainable ML, simulation, and optimization, and mentoring other data scientists and engineers. Our Vision of You: • You have a MS or PhD degree in Computer Science, Statistics, or a related field, and 5+ years of industry or equivalent experience. • You have significant experience working with distributed data processing frameworks such as Spark. Experience with Spark's MLlib, AWS, Databricks, and MLFlow are a plus. • You have strong programming skills in at least one object-oriented programming language (e.g., Python, Scala, Java, C++, Go). • You understand the entire lifecycle of machine learning product development, from inception to production, and have experience deploying and running ML models in real products. • You have a strong statistical background and practical experience with experimentation (A/B testing) and causal inference. • You are pragmatic, not stubborn with your solutions, and have the mindset of “get the job done.” • You are hands-on, able to quickly pick up new tools and languages, and are excited about building things and experimenting. • You go above and beyond to help your team, you are honest, admit mistakes, and own fixing them. • You are a motivated and talented craftsperson: always looking to sharpen and adapt your skills. Key Responsibilities: Machine Learning Engineer, Data Science About the Team Data is at the core of our company's strategy. It drives ourselves and our customers to the highest levels of success. We use it for everything from customer health scores and revenue dashboards, to operational metrics of our AWS infrastructure, to helping increase product engagement and user productivity through natural language understanding, to predictive analytics and causal inference via experimentation. As our customer base continues to grow, we are looking towards new ways of leveraging our data to deeper understand our customers’ needs and deliver new products and features to help continuously improve their customer engagement workflows. The mission of the Data Science team is to enable continuous optimization by reconstructing customer engagement workflows from data, developing metrics to measure success and efficiency, and providing insights and tools to support execution and optimization of these workflows. As a member of the team, you will work with other Data Scientists, Machine Learning Engineers, and Application Engineers to define and implement our strategy for delivering on this mission. Your Daily Adventures Will Include: • Designing, developing, and deploying machine learning and recommendation applications to production. • Designing and implementing state-of-the-art models for forecasting, causal inference, and optimization. • Building large-scale simulation systems to help leaders conduct what-if analysis. • Working with internal and external customers to understand their pain points and brainstorm solutions. • Ensuring the data that feeds into our machine learning models is reliable, accurate, and punctual. • Working alongside experienced engineering, design, and product teams to help deliver new customer-facing features and products. • Serving as an expert in areas like forecasting, causal inference, explainable ML, simulation, and optimization, and mentoring other data scientists and engineers. Our Vision of You: • You have a MS or PhD degree in Computer Science, Statistics, or a related field, and 5+ years of industry or equivalent experience. • You have significant experience working with distributed data processing frameworks such as Spark. Experience with Spark's MLlib, AWS, Databricks, and MLFlow are a plus. • You have strong programming skills in at least one object-oriented programming language (e.g., Python, Scala, Java, C++, Go). • You understand the entire lifecycle of machine learning product development, from inception to production, and have experience deploying and running ML models in real products. • You have a strong statistical background and practical experience with experimentation (A/B testing) and causal inference. • You are pragmatic, not stubborn with your solutions, and have the mindset of “get the job done.” • You are hands-on, able to quickly pick up new tools and languages, and are excited about building things and experimenting. • You go above and beyond to help your team, you are honest, admit mistakes, and own fixing them. • You are a motivated and talented craftsperson: always looking to sharpen and adapt your skills. • Machine Learning, AWS, Python, (Good to have Mllib/MLFlow)