The Coca-Cola Company
The Coca-Cola Company
The Coca-Cola Company 1886-yilda tashkil etilgan global ichimliklar kompaniyasidir. Uning mahsulot portfeliga gazlangan ichimliklar, suv va boshqa gidratatsiya mahsulotlari, qahva va choy, sharbatlar, sutli ichimliklar hamda tayyor alkogolli ichimliklar kiradi. Kompaniyaning 200 dan ortiq brendni o‘z ichiga olgan portfeli 200 dan ziyod mamlakatda sotiladi. Kompaniya faoliyati suv resurslaridan mas’uliyatli foydalanish, barqaror qishloq xo‘jaligi, mahsulotlardagi shakar miqdorini kamaytirish va The Coca-Cola Foundation tomonidan qo‘llab-quvvatlanadigan jamoatchilik tashabbuslarini ham qamrab oladi. Keng xalqaro xodimlar jamoasi va turli bozorlardagi ishga qabul qilish imkoniyatlariga ega The Coca-Cola Company ish joyiga yondashuvining bir qismi sifatida inklyuzivlik, qulaylik va ijtimoiy ta’sirni ta’kidlaydi.

Senior Manager, Data Science and Agentic AI – Mexico City

Lead predictive modeling and agentic AI development on Coca-Cola’s Azure and Microsoft Fabric platforms. Scale data-driven decisions across LATAM commercial and enterprise functions.

Tavsif

  • Create and scale data science models and AI agents that convert LATAM data into actionable decisions
  • Develop predictive and prescriptive models for forecasting, elasticity, segmentation, and next-best-action recommendations
  • Move analytical use cases from proof of concept to production through experimental design, feature engineering, validation, and impact measurement
  • Examine complex, high-volume datasets to uncover trends, drivers, risks, and optimization opportunities
  • Build LLM-powered assistants, copilots, and multi-step agentic workflows
  • Use RAG, prompt and context engineering, tool and function calling, orchestration, multi-agent architectures, and semantic or ontology grounding
  • Deploy and operate agents with Azure AI Foundry, Microsoft Fabric, Azure ML, and the Nexus AI platform
  • Version agents and integrate them into business processes
  • Test and strengthen agents with evaluation sets and guardrails while monitoring accuracy, hallucinations, bias, drift, and token costs
  • Implement Responsible AI and governance practices covering lineage, auditability, and safe, compliant use
  • Collaborate with Commercial, Marketing, Finance, Supply Chain, Strategy, data engineering, and governance teams
  • Apply MLOps methods, including CI/CD, monitoring, and reproducible workflows
  • Turn technical findings into business narratives and recommendations for senior stakeholders
  • Mentor analysts, develop reusable patterns, and encourage experimentation and evidence-based decisions

Talablar

  • Bachelor’s degree in Data Science, Statistics, Computer Science, Engineering, Analytics, or a related discipline
  • At least five years of experience in data science, machine learning, or advanced analytics, including delivering production models
  • Hands-on experience developing generative AI and agentic applications using LLMs, RAG, prompt and context engineering, tool calling, and agent orchestration
  • Strong foundations in Python, pandas, scikit-learn, a modern deep learning or LLM framework, SQL, statistics, and experimentation
  • Experience with cloud data and AI platforms, preferably Azure, including Azure ML and Azure AI Foundry or OpenAI
  • Experience with Microsoft Fabric or Databricks, MLOps, and vector databases
  • Knowledge of Responsible AI and governance practices, including evaluation, guardrails, bias and drift monitoring, lineage, and cost management
  • Strong communication skills and commercial understanding
  • Ability to work across matrixed global teams while managing multiple priorities in a fast-paced setting
  • Familiarity with the beverage and system landscape, including RGM, Commercial, and Revenue, is advantageous
  • A master’s degree is advantageous
  • Knowledge of the EU AI Act and NIST AI RMF is advantageous

Imtiyozlar

  • Purpose-led work influencing LATAM growth and decision-making
  • Opportunity to work with Global DTS, Europe, and leading bottlers
  • Career development as a data science and agentic AI leader
  • Participation in a globally connected organization
  • Culture of continuous learning
  • Inclusive workplace guided by the company’s purpose

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