Data Scientist III

Fetcherr • Atlanta, GA

2h

About The Position

This is an individual contributor role focused on building Fetcherr’s product, rather than conducting pure research. As part of a team of Data Software Engineers, the Data Scientist will contribute directly to code and own well-scoped modeling problems end to end—from exploring market data and designing features to validating models and deploying them to production. The work supports pricing, inventory, and network optimization engines that make real-time decisions.

The role sits at the intersection of applied AI and production software and involves close collaboration with data scientists, ML and data engineers, and product teams. The successful candidate will help improve model performance and business impact while keeping Fetcherr’s glass-box principles central: model logic and outcomes should be explainable to commercial teams and customers. The role also contributes to the technical direction of the modeling stack as Fetcherr expands across customers, verticals, and product lines.

Requirements

• At least 5 years of full-time experience as a Data Scientist, Applied Scientist, ML Engineer, or in a similar role building models that run in production. Lab, proof-of-concept, prototype, academic, and part-time experience does not count toward this requirement.
• Strong Python programming skills and production-grade coding practices, including testing, code review, and version control.
• A solid foundation in statistics, machine learning, and time-series forecasting, with sound judgment on model validation and experiment design.
• Strong SQL skills and experience working with large relational and non-relational datasets.
• Experience and comfort with AI-assisted software development, and the ability to write and reason about code independently.
• Experience with cloud platforms and modern data warehouse and lakehouse technologies; GCP and BigQuery are preferred.
• Familiarity with orchestration tools such as Airflow or Dagster, and with CI/CD practices for ML and data pipelines.
• A strong analytical mindset and a pragmatic, get-it-done approach.
• Excellent collaboration and communication skills, with comfort working cross-functionally with engineering and product teams.

Nice To Haves

• Experience with dynamic pricing, revenue management, or optimization problems.
• Experience in travel, e-commerce, logistics, or other real-time decisioning domains.
• Exposure to MLOps practices such as model registries, monitoring, and automated retraining.
• Experience with real-time OLAP engines such as ClickHouse.
• Experience in a Software-as-a-Service environment.

Responsibilities

• Develop, validate, and iterate on demand forecasting, pricing, and optimization models using large-scale, high-velocity market data.
• Explore and analyze data from diverse internal and external sources to uncover signals, define features, and identify opportunities to improve model accuracy and business impact.
• Design and run offline experiments, backtests, and online evaluations to measure model performance and profit uplift.
• Write production-grade Python code and work with ML and data engineers to productionize models that are reliable, observable, and cost-efficient.
• Monitor deployed models for drift, accuracy, and data quality issues, and troubleshoot and fix problems quickly.
• Build models whose logic and outcomes can be explained to commercial teams and customers.
• Partner with product and commercial stakeholders to translate business problems into modeling approaches and communicate results.
• Contribute to the technical direction of the modeling stack as Fetcherr scales across customers, verticals, and product lines.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed