About the Role
We are looking for a talented Mid-Senior Data Scientist (Forecasting & Pipelines) to join our remote team in Latin America. In this role, you will leverage your expertise in data science to design and implement machine learning workflows that directly impact supply chain and retail decision-making. As a Mid-Senior Data Scientist, you will be responsible for developing accurate forecasting models that enhance operational efficiency and drive business growth.
What You'll Do
- Design, build, and maintain automated data pipelines and production-grade machine learning workflows.
- Develop and optimize demand and inventory forecasting models using advanced time-series and statistical techniques.
- Architect and manage large-scale datasets in Snowflake, ensuring high performance, reliability, and data integrity.
- Write complex, optimized SQL queries for data transformation and feature engineering.
- Translate supply chain and retail business requirements into scalable technical solutions and actionable insights.
- Implement best practices in code quality, documentation, testing, and statistical validation.
- Collaborate cross-functionally with business stakeholders and mentor junior team members when needed.
Requirements
- 4+ years of professional experience in Data Science or Machine Learning Engineering roles.
- Expert-level proficiency in Python (Pandas, NumPy, Scikit-learn, Prophet, Statsmodels, XGBoost or similar forecasting libraries).
- Advanced SQL skills with experience optimizing complex queries for analytics and ML workflows.
- Hands-on experience with Snowflake (experience with Snowpark or Tasks is a strong plus).
- Strong foundation in time-series analysis, statistical modeling, and working with large, messy datasets.
- Experience deploying scalable forecasting models into production environments.
- Bachelors or Masters degree in Computer Science, Statistics, Engineering, Economics, or a related quantitative field.
Nice to Have
- Direct experience in Supply Chain (inventory optimization, logistics, replenishment planning) or Retail (demand planning, pricing, seasonality modeling).
- Experience with orchestration tools such as Airflow or Dagster.
- Exposure to MLOps practices, CI/CD pipelines, and model monitoring in production environments.
- Experience working in fast-paced, data-driven environments supporting operational teams.
What We Offer
- Competitive salary in line with market rates.
- Full-time remote work flexibility.
- Opportunity to work on impactful projects in a growing company.
- Collaborative and inclusive team culture.
- Professional development opportunities and mentorship.
This Mid-Senior Data Scientist role offers a unique opportunity to work remotely on impactful forecasting projects. Join a collaborative team and drive business growth with your expertise.
Who Will Succeed Here
Proficient in Python and its data manipulation libraries like Pandas and NumPy, with hands-on experience in building and optimizing predictive models using scikit-learn and XGBoost.
Self-motivated and disciplined, capable of thriving in a remote work environment, effectively managing time and projects while collaborating asynchronously with team members across different time zones.
Strong understanding of data pipeline orchestration using tools like Airflow, with a mindset geared towards implementing MLOps best practices to streamline model deployment and monitoring.
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