Data Engineering Scientist

THE COMPANY: BIRDY GREY

POSITION: Data Engineering Scientist

REPORTS TO: Director, Data & Analytics

LOCATION: Remote

Headquartered in Los Angeles, CA with an office in New York, NY, Birdy Grey supports remote work for eligible roles. We ask that all employees travel to either office once a quarter. This role is not eligible for visa sponsorship. #LI-Remote

We're looking for a Data Engineering Scientist who thrives on variety. This isn't a role where you'll specialize in one narrow area, you'll be building pipelines, analyzing data, creating dashboards, and  developing models. If you are energized by wearing multiple hats, statistically rigorous, hungry to learn new things, and eager to observe the direct impact of your work, this role is for you.

SCOPE OF RESPONSIBILITIES

• Data Science (30-40%)

  • Lead the application of statistical and machine learning methodologies (using Python and relevant frameworks) to solve core business problems, focusing on predictive and prescriptive outcomes
  • Co-design rigorous A/B and multivariate experiments, ensuring statistical validity to accurately measure the impact of product and business changes
  • Identify opportunities where machine learning or advanced analytics can add value
  • Prototype data-driven solutions to business problems

  Data Engineering (20-30%)

  • Architect and Deploy robust data pipelines to collect, transform, and load data from various sources
  • Design and optimize data storage solutions and database schemas
  • Ensure data quality, reliability, and accessibility across the organization
  • Automate repetitive data processes and workflows
  • Establish and enforce data governance and security standards within our Cloud environment

  Data Analytics (30-40%)

  • Serve as the embedded strategic data partner for key business teams, translating complex challenges into measurable analytical projects
  • Design and manage high-impact, self-service business intelligence assets (primarily in Looker) that accelerate organizational decision velocity
  • Conduct ad-hoc analyses to uncover insights and opportunities
  • Translate complex findings into clear, actionable recommendations

THE RIGHT CANDIDATE: QUALIFICATIONS & PERSONAL ATTRIBUTES

EDUCATION: Bachelor’s Degree Required 

EXPERIENCE / REQUIREMENTS:

• 5+ years of hands-on experience in a data science, data engineering, data analyst, analytics engineering, or ML role
• Expert SQL skills. Must be adept at designing, optimizing, and tuning complex queries, stored procedures, and scripts, specifically utilizing analytic window functions, CTEs, and advanced join techniques
• Expertise with Python (preferably) or R for data analysis and automation
• Expertise with at least one data visualization tool, preferably Looker 
• Experience with Cloud data platforms, DevOps, MLOps (AWS, GCP, Azure)
• Knowledge of data orchestration tools (Airflow, Prefect, dbt, Dagster, etc.)
• Experience with ML frameworks (scikit-learn, TensorFlow, PyTorch)
• Experience with version control (Git) and software engineering best practices
• Familiarity with marketing analytics, retail, and econometric principles
• Understanding of basic statistics and when to apply different analytical approaches
• Ability to communicate technical concepts to non-technical stakeholders
• Comfortable with ambiguity and figuring things out independently

NICE TO HAVES:

• Start-up experience 
• Interest in bridal and fashion
• Experience with ticketing systems and change management processes
• Interest in increasing productivity via Automation & AI
• Start-up or D2C/e-commerce experience