Senior Data Scientist

This is a fully remote position, open to applicants in United States.

📋 Description

• Design and execute scalable batch and real-time data processing systems across extensive and intricate datasets.

• Construct and enhance ETL and streaming data pipelines utilizing contemporary GCP big data technologies.

• Assist in development decisions regarding model selections, data architecture, data modeling, pipeline orchestration, analytics infrastructure, and production systems.

• Create statistical models and analytical capabilities that facilitate product intelligence and operational insights.

• Design and uphold production-grade data workflows employing technologies like Airflow, Dataflow, PubSub, and PySpark.

• Contribute in various areas of the data ecosystem, including data engineering, monitoring and governance, visualization, and analytics tools.

• Implement monitoring, observability, and governance practices for data quality, pipeline reliability, and production health.

• Collaborate closely with Engineering to operationalize scalable data infrastructure and analytics systems.

• Work together with Product to develop intelligent, data-driven product capabilities and enhance user experiences.

• Serve as a thought partner across data engineering, analytics, infrastructure, and applied modeling initiatives.

• Assist in evolving internal tools and frameworks that enhance scalability, reliability, and operational efficiency across the platform.

⛳️ Requirements

• 7–10+ years of experience as a Data Scientist, Applied Scientist, Data Engineer, or Machine Learning Engineer, with responsibility for production systems.

• Significant experience in constructing and managing large-scale data pipelines and distributed data processing systems.

• Practical experience within the GCP ecosystem, particularly with big data services such as Dataproc, Dataflow, PubSub, and related storage and data lake technologies.

• Strong command of Python, PySpark, and modern data processing frameworks.

• Experience in multiple disciplines of the data stack, including data engineering, analytics, infrastructure, monitoring/governance, APIs, and visualization.

• Familiarity with real-time or streaming systems and orchestration frameworks like Airflow and Apache Beam/Dataflow.

• Solid foundation in statistical modeling, analytics, and applied data science techniques.

• Experience in designing and maintaining scalable ETL workflows and production data infrastructure.

• Knowledge of monitoring, observability, governance, and reliability practices for production data systems.

• Ability to excel in highly cross-functional settings and address a broad range of technical challenges.

• Proven versatility — a background encompassing various types of data applications, infrastructure, and analytics work is highly regarded.

• Experience collaborating closely with Product and Engineering to deliver customer-facing capabilities.

• Excellent written and verbal communication skills.

• Nice-to-have: Experience with Databricks.

🏝️ Benefits

• Generous paid time off

• Paid company holidays

• Paid floating holidays

• Paid parental leave

• Paid sick time and paid family leave for applicable states

• Health insurance - medical, dental, and vision with HSA option

• LifeWorks Employee Assistance Program

• Company-provided life insurance

• AD&D

• STD/LTD and additional supplemental life insurance options

• 401(k) and Roth retirement saving accounts

• Monthly wellness benefit reimbursement