Staff Data Scientist

7+ years of experience in a data science or machine learning role 3+ years experience in mentorship or leadership roles, with the proven ability to provide guidance and support as a subject matter expert to other data team members and stakeholders Demonstrated experience leading ML initiatives from conception through production across multiple business domains Proven track record of designing, building, deploying, and maintaining production-grade machine learning systems using modern MLOps practices Deep understanding of machine learning libraries (scikit-learn, TensorFlow, etc.) and algorithms Strong foundation in statistics and applied statistical analysis, including A/B testing, hypothesis testing, Bayesian inference, time series modeling, and multivariate methods Proficient in Python and SQL, with extensive experience manipulating large datasets and developing performant data pipelines Experience with machine learning platforms/services such as SageMaker, Bedrock, Gemini, Vertex, Azure Machine Learning, Databricks etc. Demonstrated ability to transform ambiguous business problems into actionable ML solutions; comfortable operating in high-uncertainty environments Experience defining technical standards for experimentation, monitoring, and model performance in production environments Ability to manage and prioritize projects, balancing short-term needs with long-term strategic goals Strong communication skills, with the ability to clearly articulate complex technical concepts to technical and non-technical audiences Experience with data visualization and BI tools such as Looker, Tableau, or equivalent BS in Data Science, Statistics, Mathematics, Economics, Computer Science, Information Management or equivalent experience

Drive the full machine learning lifecycle as a key technical leader. Own and continuously improve ML systems in production, working with engineering to ensure high availability, reliability, and performance. Partner with our Product and Engineering teams to translate ambiguous problems into clear, actionable requirements. Apply advanced data mining and machine learning techniques, such as natural language processing, deep learning, and neural networks, to solve complex business problems Proactively engage with senior leadership to identify opportunities where data science can drive innovation, efficiency, or competitive differentiation. Regularly communicate findings and recommendations clearly and effectively to both technical and non-technical audiences, tailoring content to the stakeholder context. Collaborate with Data team members and Product leaders to shape the data science strategy and roadmap for Platform Science. Mentor, coach, and level up peers and stakeholders, fostering a culture of continuous learning and technical excellence.