Data Scientist

Data Scientist – Supply Chain Industry We are: Wizeline, a global AI-native technology solutions provider, develops cutting-edge, AI-powered digital products and platforms. We partner with clients to leverage data and AI, accelerating market entry and driving business transformation. As a global community of innovators, we foster a culture of growth, collaboration, and impact. With the right people and the right ideas, there's no limit to what we can achieve. Are you a fit? Sounds awesome, right? Now, let's make sure you're a good fit for the role: We are looking for a Data Scientist with a strong background in advanced analytics and a passion for solving complex supply chain problems. In this role, you will work on high-impact initiatives involving demand forecasting, inventory optimization, and logistics analytics. You will partner closely with business and operations teams to transform data into actionable insights that improve end-to-end supply chain performance. Location & Work Model Location: Mexico City (CDMX) Office: Santa Fe, Cuajimalpa Work model: Hybrid — 1 day per week onsite / 4 days remote Key Responsibilities Apply advanced analytics, statistical modeling, and machine learning to solve complex supply chain problems such as demand forecasting, inventory optimization, resource allocation, and logistics network analysis. Design, develop, and maintain end-to-end data science solutions, from data exploration and feature engineering to model deployment and monitoring. Build and optimize data pipelines and analytical workflows using Azure Databricks and large-scale datasets. Translate business questions from sales, logistics, and operations teams into quantitative, actionable analyses. Validate hypotheses, identify patterns, and design data-driven solutions that improve key supply chain KPIs. Collaborate closely with Supply Chain, Finance, and Sales teams to align analytical solutions with business objectives. Document analytical processes, models, and assumptions, and share knowledge with the analytics team. Continuously evaluate data quality, analytical processes, and tooling, proposing improvements where needed. Must-have Skills (Remember to include years of experience) Bachelor's Degree in Data Science, Statistics, Engineering, Mathematics, Computer Science, or a related field. 3–5+ years of experience in Data Science, Analytics Engineering, or similar roles. Strong proficiency in Python and SQL, including experience with data science and ML libraries such as Pandas, PySpark, Scikit-learn, and MLflow. Hands-on experience working with large-scale datasets and pipelines in Azure Databricks. Solid understanding of statistical modeling, time series analysis, clustering, optimization, or simulation techniques. Experience applying analytics to real-world business problems in demand planning, inventory management, logistics, or routing is a strong plus. Ability to work autonomously, owning projects end-to-end and making informed decisions with minimal supervision. Strong analytical and problem-solving skills, with the ability to operate in environments with high uncertainty. Excellent communication skills, capable of explaining models, assumptions, and results to non-technical stakeholders. English level: Advanced / Fluent (spoken and written). Nice-to-have: AI Tooling Proficiency: Leverage one or more AI tools to optimize and augment day-to-day work, including drafting, analysis, research, or process automation. Provide recommendations on effective AI use and identify opportunities to streamline workflows. Experience with advanced forecasting methodologies, operations research (OR), or simulation techniques applied to supply chain problems. Familiarity with optimization solvers or libraries. Exposure to cloud-based data architectures beyond Azure (e.g., AWS, GCP). What we offer: A High-Impact Environment Commitment to Professional Development Flexible and Collaborative Culture Global Opportunities Vibrant Community Total Rewards *Specific benefits are determined by the employment type and location. Find out more about our culture here.