Design, train, and evaluate ML models (classification, regression, time series, uplift modeling) for forecasting, propensity, churn, pricing, and optimization use cases Build prescriptive analytics frameworks (optimization, scenario simulation, A/B testing) to translate model outputs into decision recommendations Implement CI/CD for data & model artifacts, enabling reproducible environments and automated testing Collaborate with analytics engineers to design feature stores, materialized views, and semantic layers aligned to domain models Establish best practices for data quality, documentation, governance (RBAC, tags, masking & row-access policies), and cost/performance management Provide consulting to departments without dedicated data teams—coaching on data literacy and ML adoption 4+ years in applied analytics/ML building predictive and prescriptive solutions end-to-end Bachelor's degree in Applied Mathematics, Statistics, Data Science, Computer Science or equivalent field demonstrating formal training in statistics and quantitative methods Successfully deployed at least 2 ML models into production, managing all stages of the model lifecycle such as development, deployment, monitoring, retraining Strong hands-on Python (pandas, NumPy, scikit-learn) and production code quality (packaging, testing, logging) Mastery in data mining using SQL Demonstrated success deploying and operating models at scale in Snowflake or equivalent cloud data platform Snowflake proficiency: Snowpark (Python), UDFs, Stored Procedures, and Tasks Experience with Snowflake-native ML workflows and integrated Streamlit apps for rapid prototyping Master's degree in Data Science, Statistics, Computer Science, or related field Familiarity with dbt for analytics engineering and integration points with Snowflake Knowledge of optimization libraries (scipy.optimize, PuLP, OR-Tools) and causal inference frameworks Experience with feature stores, model registries, and orchestration tools (Airflow, Prefect) Exposure to GPU-backed training and model explainability techniques (SHAP, permutation importance) The chance to use your skills and imagination to push the boundaries of what´s possible. To build solutions never seen before to some of the world's toughest problems. You´ll be challenged, but you won't be alone. You´ll be joining a team of diverse innovators, all driven to go beyond the status quo to craft what comes next. What happens once you apply? Click Here to find all you need to know about what our typical hiring process looks like. We truly believe this approach drives innovation, which is essential for our future growth. DISCLAIMER: The above statements are intended to describe the general nature and level of work being performed by employees in this position. They are not an exhaustive list of all responsibilities, duties and skills required for this position, and you may be required to perform additional job tasks as assigned. Primary country and city: United States (US) || Boise (ID) (Country/ City) Job details: Data Scientist