Data Scientist

While you will use Snowflake and SQL for data access and preparation, your primary focus will be on developing robust, scalable, and innovative models that deliver measurable business impact. You will be expected to contribute across the entire model lifecycle—from exploratory analysis and feature engineering in notebooks through deployment and monitoring to continuous refinement and improvement—working closely with teammates who provide engineering, data, and infrastructure support.This role requires close collaboration with cross-functional partners such as business leaders, analysts, product managers, and engineers to identify high-value opportunities for AI/ML integration. You will help translate complex analytical insights into actionable strategies, with a strong emphasis on innovation, critical thinking, and advanced modeling approaches that align with business objectives and drive meaningful organizational outcomes.**JOB DUTIES**:- Develop and deploy predictive models to support customer experience, demand forecasting, operations optimization, customer behavior analysis, and revenue trends in B2B/DX environments.- Design and implement production-grade machine learning models using both classical algorithms (SVM, Gradient Boosting, Random Forests, etc.) and modern deep learning (LSTM, Transformers).- Build, monitor, and optimize recommendation systems that enhance personalization and customer engagement.- Transition models from exploratory notebooks to production-ready artifacts (e.g., serialized pickles or containers) with proper engineering practices.- Ensure smooth end-to-end MLOps integration, including CI/CD pipelines, model versioning, deployment, monitoring, and retraining.- Perform advanced statistical analysis on business metrics to deliver specialized reporting and actionable insights.- Contribute to experimentation and model evaluation through A/B testing, KPI definition, and impact measurement.- Collaborate with cross-functional teams to identify opportunities for AI/ML integration into business processes and products.- Communicate results, assumptions, model limitations, and business recommendations to non-technical and technical stakeholders.- Share knowledge with peers, explain modeling approaches, and foster a data-driven culture across teams.Promote and advocate for data science best practices within the organization.**YOU MUST HAVE**:- 3+ years of hands-on experience in applied data science / machine learning, ideally in B2B, Retail, or eCommerce environments.- Advanced **English**proficiency for communication and documentation.- _SQL expertise _including the ability to write queries, procedures, and functions.- Experience with _Python data science and machine learning _libraries including Scikit-learn, Pandas, NumPy, Matplotlib/Seaborn, and other relevant frameworks for model development and data analysis.- Deep knowledge of classical ML algorithms (GBMs, Random Forests, SVMs, etc.).Strong analytical and problem-solving skills, always linking technical work to business impact.**WE VALUE**:- Strong programming skills in Python (preferred) and/or R, with comfort in shell scripting (PowerShell, Bash, Linux).- Experience with Snowflake (preferred) or a comparable cloud data warehouse.- Practical experience with deep learning architectures, including sequence models (LSTM) and Transformers.- Hands-on experience building or improving recommendation systems.- Familiarity with MLOps workflows: CI/CD pipelines, model versioning, deployment, monitoring, and retraining; proven ability to move models from notebooks to production.- Understanding of data engineering concepts and tools such as data pipelines, dbt, workflow schedulers (e.g., Apache Airflow), and data buffering.- Familiarity with Azure cloud products and ML/AI services.- Knowledge of eCommerce attribution models and platforms (Google Analytics, Fullstory, Quantum Metrics, etc.).- Experience in logistics, pricing, or customer experience analytics.- Proficiency with GitHub or similar version control systems.- Experience in Agile Scrum environments and iterative, collaborative delivery.- Strong collaboration skills and the ability to contribute to a data-driven organizational culture.Curiosity, adaptability, and commitment to data science best practices.- **WHAT'S IN FOR YOU**:- Benefits that go beyond Mexican labor law, ensuring your well-being and peace of mind.- A collaborative and inclusive work environment where your contributions are valued.- Opportunities for continuous professional growth and skill development through training, mentoring, and challenging projects.- Access to cutting-edge tools, resources, and a supportive team to help you excel.The chance to work with a global, innovative company shaping the future in its industry.LI-AA1LI-Hybrid