Platform Science needs a Staff Data Scientist to process large amounts of raw data into strategic insights for Product, Engineering, and Leadership teams, and to drive data-driven decision making and shape the company's data science and machine learning capabilities.
Requirements
- 7+ years of experience in a data science or machine learning role
- 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.
- Experience with data visualization and BI tools such as Looker, Tableau, or equivalent
- Experience with Snowflake
- Experience with Data Build Tool (dbt)
- Experience with advanced ML/AI techniques such as deep learning and reinforcement learning
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.
- Apply advanced data mining and machine learning techniques, such as natural language processing, deep learning, and neural networks, to solve complex business problems
- 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.
- Define standards for observability, monitor model drift, and implement retraining and alerting pipelines.
- Translate ambiguous problems into clear, actionable requirements.
- Scope and prioritize ML opportunities that deliver measurable business value.
Other
- 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
- 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
- BS in Data Science, Statistics, Mathematics, Economics, Computer Science, Information Management or equivalent experience
- At this time we only consider candidates in these states: AL, AR, AZ, CA, CO, FL, GA, ID, IL, KY, MA, MD, MI, MN, MO, NC, NH, NV, NY, OH, OK, OR, PA, SC, TN, TX, UT, VA, WA, and WI. In the future we plan to add more states.
