What You’ll Do

• You’ll help our data science team grow by sharing your ideas, challenging status quo, and influencing the direction of the team  
• You’lldemonstrate a broad knowledge of ML approaches and you are pragmatic about solutions. E.g., you create business value and fit models  
• You’ll work across supervised, unsupervised, and deep learning approaches while being comfortable using inferential statistics, time series, LLMs, or computer vision approaches to solve a given problem (we don’t expect expertise in all!)  
• You’ll design, engineer, test, document, and explain production ML systems in Azure, Python, SQL, and Git  
• You’ll take the lead gathering input from non-technical customer stakeholders and senior IT leadership to plan what to build and set project scope  
• You’ll frame complex problems and propose options to either use data when it’s available or pursue alternatives when it’s not  
• You’ll take the lead in technical design discussions, remove blockers, and align stakeholders  
• You’ll use Big Data tools (Databricks, Spark, Azure, SQL, Python) to carry out supporting analyses and build production solutions  
• You’llsubmityour daily hours billed to cloud-based project management software, Kantata, for time tracking  
• You’ll fit, tune, test, validate, and deploy ML models in an MLOps setting to solve real-world problems  
• You’ll discuss project issues and topics simply when presenting to customers   

What You’ll Need

• Strong coding skill in SQL and Python (especially pandas, numpy, scikit-learn)  
• Over 5 years of experience in the applied Machine Learning and Data Science field. And at least 3 years of experience owning ML systems from idea to maintenance  
• Relative experience (~10+ projects) in cloud development. Azure is preferred but AWS, GCP, or other relative cloud platform experience is acceptable  
• Professional experience using Databricks and Spark  
• Demonstrable thought leadership evidenced by an active GitHub, blog posts, or publication record  
• Deeply curious about the world  
• Willing to challenge the status quo to propose improvements  
• Motivated by challenge and do not shy away from potential failure  
• Can communicate simply and intuitively to diverse audiences with varying technical background 
• Proven success with--and interest in--owning end-to-end projects solo but knowing when to escalate and delegate  
• Experience with--and interest in—developing in a production MLOps setting  
• Practical experience with tools for the ML lifecycle, including EDA, data prep, data verification, modeling, testing, deploying, and relevant object-oriented software development tasks  
• Experience using data visualization to understand and persuade   

What Will Set You Apart

• Having most of the above characteristics and experiences  
• Above average experience in cloud development  
• Strong software engineering experience  
• Experience working in a professional services organization  
• Product mentality but a professional services approach