Data Scientist – Production Engineering

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

📋 Description

• Enhance the performance, scalability, and reliability of current data science models and systems.

• Convert research-level or prototype data science code into implementations suitable for production.

• Manage large datasets while optimizing memory usage, runtime, and computational costs.

• Assist in the development and maintenance of production data pipelines and workflows.

• Work closely with fellow data scientists to ensure model intent, accuracy, and assumptions are upheld while enhancing the quality of implementations.

• Identify and fix issues within production or near-production data science workflows.

• Strengthen the robustness, monitoring, and maintainability of deployed models and pipelines.

• Facilitate iterative enhancements to models and systems as business requirements evolve.

⛳️ Requirements

• A Bachelor’s degree or higher in Data Science, Computer Science, Statistics, Mathematics, or a similar quantitative discipline, along with 3+ years of experience handling real-world, industry, or production data in data science, applied ML, or analytics roles.

• Proven track record of contributing to production data science or analytics systems, beyond exploratory or academic projects.

• Proficient programming skills in Python with experience in writing maintainable, production-grade code.

• Familiarity with large datasets and performance-critical workflows.

• The code word is #becordial.

• Previous experience with data pipelines and orchestration frameworks like Dagster or Airflow.

• Expertise in cloud platforms, particularly AWS services (Glue, Athena, ECS, S3 Tables, etc.) for scalable data processing and model deployment.

• Practical experience with modern data warehouse solutions (Snowflake, BigQuery, etc.), including query optimization, clustering strategies, and cost management.

• Experience with big data technologies and distributed computing frameworks for managing enterprise-scale event datasets.

• Strong grasp of data science principles, including statistics and modeling concepts, enabling collaboration with research-focused data scientists.

• Ability to work independently and quickly adapt to an existing codebase and system.

• Experience in small, agile teams where ownership and autonomy are valued.

🏝️ Benefits

• Comprehensive benefit package (medical/dental/vision/life).

• 401k matching.

• Flexible time off policy.

• Paid company holidays.

• Annual company conference.

• Childcare reimbursement.

• Yearly reimbursements for continued education.

• Emphasis on a healthy work/life balance.

• Strong commitment to diversity, equity, and inclusion efforts.

• Overall culture of respect and openness.