Staff Data Scientist

Summary

Join Platform Science as a Staff Data Scientist to leverage your expertise in processing large datasets and building machine learning models. You will lead the design and implementation of ML models, ensuring their scalability and reliability within production environments. Collaborate with Product and Engineering teams to translate business needs into actionable requirements, and proactively identify opportunities for data-driven innovation. Communicate findings effectively to both technical and non-technical audiences, mentoring team members and shaping the data science strategy. This role requires a strong foundation in statistics, machine learning, and programming, along with experience in leading ML initiatives and managing projects. The ideal candidate will possess excellent communication skills and a proven ability to translate complex technical concepts into easily understandable terms.

Requirements

• 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

Responsibilities

• Drive the full machine learning lifecycle as a key technical leader. Shape architectural decisions, guide system design and model selection, and oversee the deployment of scalable, production-ready models using robust MLOps practices
• Own and continuously improve ML systems in production, working with engineering to ensure high availability, reliability, and performance. Define standards for observability, monitor model drift, and implement retraining and alerting pipelines
• Partner with our Product and Engineering teams to translate ambiguous problems into clear, actionable requirements. Scope and prioritize ML opportunities that deliver measurable business value
• 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. Influence product and business strategy through data-driven insights
• 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. Lead the organization in establishing best practices for launching and analyzing ML products
• Mentor, coach, and level up peers and stakeholders, fostering a culture of continuous learning and technical excellence

Preferred Qualifications

• Expertise with Looker
• Experience with Snowflake
• Experience with Data Build Tool (dbt)
• Experience with advanced ML/AI techniques such as deep learning and reinforcement learning

Benefits

• Medical, dental, and vision insurance
• Short-term and long-term disability insurances
• AD&D and life insurance
• 401k plan
• Paid vacation, sick leave and holidays
• Six weeks of paid parental leave