Remote Data Scientist​/Machine Learning; Senior, E-Commerce, Google Cloud

Remote Data Scientist/Machine Learning (Senior, E-Commerce, Google Cloud) #22506

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Our client began as a family-run women’s apparel business in the late 1930s. Over the decades, the company has evolved into a nationally recognized fashion retailer focused on helping customers feel confident and well dressed for special moments, nights out, and everyday occasions. What started as a small operation has grown into a large retail organization with hundreds of locations, a growing team, and an ongoing expansion strategy.

They are currently looking for a proactive Data Scientist/Machine Learning to join the team.

If you’re a passionate individual and think you have what it takes to help carry this legacy forward, we encourage you to apply and join the team.

Our client began as a family-run women’s apparel business in the late 1930s. Over the decades, the company has evolved into a nationally recognized fashion retailer focused on helping customers feel confident and well dressed for special moments, nights out, and everyday occasions. What started as a small operation has grown into a large retail organization with hundreds of locations, a growing team, and an ongoing expansion strategy.

We are building a scalable data science capability to drive forecasting and optimization across multiple operations domains, including merchandise allocation, labor planning, and inventory management. You will design, develop, and product ionize predictive and prescriptive models, collaborate with data engineers to maintain robust data pipelines, and partner with business stakeholders to convert insights into actionable planning decisions

• Our client is a GCP shop, and they also leverage AWS and Azure to support their operations.
• Strong experience working on e-commerce platforms.
• Hands-on experience with Shopify.
• Contract:
  
  3 to 6 months
• Location:
  
  LATAM
• Start Date:
  
  ASAP
• The core team is based in the Los Angeles area, with additional developers located across LATAM in Brazil, Argentina, and Colombia. Working hours will follow the Pacific Time Zone.

MAIN REQUIREMENTS:

• 3+ years of practical data science / applied ML experience.
• Strong Python (pandas, Num Py, scikit-learn) and SQL (Big Query) skills.
• Experience with cloud ML platforms, preferably Google Cloud Vertex AI; familiarity with Big Query ML is a plus.
• Demonstrated experience building, validating, and deploying predictive models to production.
• Knowledge of time-series forecasting and optimization concepts; experience with planning problems is a plus.
• Familiarity with feature stores, ML pipelines, model monitoring, and reproducibility practices.
• Excellent communication skills; ability to translate business needs into data-driven solutions.

GOOD TO HAVE:

• Experience with Vertex AI Feature Store, Vertex AI Pipelines, and Vertex AI Model Monitoring.
• Experience with inventory optimization, labor planning, or retail analytics.
• Exposure to operations research / optimization techniques (e.g., linear programs, heuristics) and integration with forecasting outputs.
• Knowledge of CI/CD for ML and MLOps practices.

Required Tools & Technologies (preferred)

• Google Cloud Platform:
  Vertex AI, Big Query, Dataflow, Cloud Storage
• Python data stack: pandas, Num Py, scikit-learn
• SQL:
  Big Query SQL
• Optional: XGBoost/Light
  
  GBM, AutoML Tables, Vertex AI Pipelines

• Develop predictive models for planning problems (e.g., demand forecasting, staffing, capacity planning, inventory optimization) across multiple domains.
• Engineer features from historical data (sales, product attributes, store characteristics, labor availability, promotions, holidays) and external factors.
• Design robust evaluation strategies with time-aware splits; select business-relevant metrics (MAE, RMSE, MAPE, service level, utilization).
• Implement end-to-end ML lifecycle in Vertex AI (training, evaluation, deployment, monitoring) and manage experiments with versioning.
• Implement online and batch inference solutions; integrate predictions into replenishment, scheduling, and workforce planning systems.
• Monitor model performance and data drift; schedule retraining and maintain model version control.
• Create…