Stackline

About the Company

On a mission to fuel the future of commerce by bringing brands and customers closer together, Stackline is the leading AI-enabled retail intelligence and activation platform for the world's most innovative brands. Business leaders, product innovators, performance marketers, and financial firms trust Stackline as the single source of commerce truth. Fueled by proprietary neural networks and deep learning systems, Stackline's market insights, revenue metrics, behavioral data, and autonomous functionality create the actions that determine success or failure.

Founded in 2014 in Seattle, Stackline employs over 250 connected commerce professionals creating value for 7,000 global brands.

Listed Jobs

Company Name

Stackline

Job Title

Data Scientist I

Job Description

Job title: Data Scientist I Role Summary: Apply large language or multimodal model expertise to build and scale machine learning solutions that drive product insights and performance across a high‑volume commerce platform. Expectations: - Bachelor/PhD‑level technical knowledge in quantitative fields. - Minimum 1 year experience in data science or analytics, including model development and deployment. - Proven ability to handle large, complex datasets and deliver actionable results. - Strong collaboration with engineering, product, and stakeholder teams. Key Responsibilities: - Develop, test, and deploy LLM/LMM pipelines for multiple product lines. - Design and implement scalable machine‑learning models and experiments. - Create and maintain data quality controls and documentation of analytical workflows. - Provide informed, timely responses to internal and external data/model queries. - Translate data insights into actionable recommendations for cross‑functional teams. - Work independently on model conceptualization, prototype, validation, and production rollout. Required Skills: - Advanced proficiency in Python and SQL for data manipulation, modeling, and automation. - Experience with ML frameworks (TensorFlow, PyTorch, Spark ML) and version control (Git). - Strong statistical, probabilistic, and algorithmic foundations. - Hands‑on experience deploying ML solutions at scale. - Knowledge of LLMs or LMMs, including training, fine‑tuning, and inference. - Ability to analyze and process large, heterogeneous data pipelines. Required Education & Certifications: - PhD (or advanced Master’s) in Mathematics, Physics, Computer Science, Engineering, or related technical discipline. - Valid certifications in data science or machine‑learning platforms are a plus but not mandatory.

Seattle, United states

On site

Fresher

25-11-2025