Job Description
Ciudad de México
Nivel de estudios
Bachelor’s Degree in Computer Science, Computer Engineering, Data Science, Artificial Intelligence, Industrial Engineering or equivalent. Advanced degree preferred.
Experiencia Requerida
5+ years delivering enterprise-level Data Science solutions
Habilidades
Soft Skills
- Team Player: Excellent communication and interpersonal skills, working effectively as part of a team and collaborating with stakeholders across different locations. Ability to tell a story with data. Ability to communicate results of advanced analytics in plain English.
- Adaptability: Thrive in a dynamic, fast-paced work environment and adapt quickly to changing business needs.
- Attention to Detail: Meticulous attention to detail, ensuring data accuracy and maintaining high-quality standards in all deliverables.
Technical Skills
- A minimum of 5 years of professional hands-on experience developing/deploying Enterprise-scale data scicene soluitons
- An understanding of cloud infrastructure for Machine Learning/AI ops., e.g., Databricks / AWS Sagemaker
- Strong problem-solving skills and the ability to troubleshoot complex data and machine learning related issues
- Solid understanding of a variety of machine learning algorithms.
- Solid understanding of developing, deploying and gaining value from Gen AI and AI (agentic) agents.
- Expert-level proficiency with Python
- Hands-on experience with machine learning and generative AI frameworks
- Experience deploying machine learning and AI applications in cloud-based solutions (AWS or Databricks).
- Strong understanding of database systems, data structures, and data processing techniques.
- Familiarity with OPC-UA, MQTT, and industrial automation protocols is a significant advantage
- Strong analytical abilities to translate business requirements into technical AI workflows
- Experience in a manufacturing or industrial environment preferred
Resumen
The Sr. Data Scientist, Digital Manufacturing uses data from production lines (including sensors), digital frontline worker solutions, and quality control systems to build and deliver advanced analytics, predictive modeling, machine learning, and AI solutions that improve manufacturing performance and reduce cost. The role applies statistical methods, data visualization, generative AI, and AI agents to help teams make data-driven decisions that increase productivity and efficiency, reduce waste, improve product quality, and lower total operating costs. Key focus areas include manufacturing process optimization, predictive maintenance, defect detection, utilities (energy/water) optimization, and process automation. You will be responsible for the entire project life cycle from conception through commissioning of projects that support advanced analytic initiatives.
Responsabilidades
1. Develop and operationally deploy advanced analytic decision support solutions (machine learning, deep learning, generative AI, Agentic agents, etc.) to that incorporate data from disparate manufacturing systems (MES, LIMS, CMMS, WMS, ERP, etc.) to drive process improvement and performance optimization.
2. Collaborate with cross-functional teams (Manufacturing, Operations, R&D, Quality, IT, etc.) to design and implement largescale data-driven solutions. Ensure data quality, integrity, and compliance with model risk standards. Partner with technical and non-technical teams to resolve data gaps, inconsistencies, support validation activities and ensure ROI is derived from
data science activities.
3. Collect, clean, and pre-process large structured and unstructured datasets to ensure they are "model-ready". Preprocess, cleanse, and manage data to ensure accuracy and quality for model input and inference.
4. Conduct Exploratory Data Analysis (EDA) using statistical techniques and data visualization to uncover patterns, relationships, and outliers. Conduct feature engineering and train/test machine learning models for real-time process monitoring/alerting, anomaly detection, quality defects and machine failure prevention/identification. Manage model lifecycle
(data prep, train, test, tune, deploy, monitor performance).
5. Design, build, and deploy AI-powered applications, chatbots, and agents. Implement Retrieval-Augmented Generation (RAG). Integrate pre-trained AI models with internal data sources and external applications.
6. Optimize AI models for speed, scalability, and cost-efficiency in production environments.
7. Monitor deployed models for performance, accuracy, and latency, implementing ML/LLM Ops and using evaluation frameworks.
8. Work with technical and non-technical teams to implement models into production and translate complex findings into actionable insights for stakeholders.
9. Maintain documentation, best practices, and knowledge repositories for analytics solutions. Monitor adoption KPIs, gather user feedback, and drive continuous improvement in analytics capabilities.
10. Stay updated with the latest AI trends to enhance organizational AI infrastructure
Location
Ciudad de Mexico, MexicoAdditional Locations
Job Type
Full timeJob Area
Operations and ProductionEqual Opportunity
Constellation Brands is committed to a continuing program of equal employment opportunity. All persons have equal employment opportunities with Constellation Brands, regardless of their sex, race, color, age, religion, creed, sexual orientation, national origin or citizenship, ancestry, physical or mental disability, medical condition (cancer or genetic characteristics), marital status, gender (including gender identity or gender expression), familial status, military or veteran status, genetic information, pregnancy, childbirth, breastfeeding, or related conditions (or any other group or category within the framework of the applicable discrimination laws and regulations).
Skills Required
- Bachelor's degree in Computer Science, Computer Engineering, Data Science, AI, Industrial Engineering or equivalent
- Advanced degree
- 5+ years delivering enterprise-level Data Science solutions
- 5+ years hands-on experience developing and deploying enterprise-scale data science solutions
- Expert-level proficiency with Python
- Experience deploying machine learning and AI applications in cloud-based solutions (AWS or Databricks)
- Understanding of cloud ML/AI infrastructure (Databricks, AWS SageMaker)
- Hands-on experience with machine learning and generative AI frameworks
- Solid understanding of a variety of machine learning algorithms
- Experience developing, deploying, and extracting value from generative AI and agentic agents
- Experience designing and implementing Retrieval-Augmented Generation (RAG) and AI-powered applications/chatbots
- Experience with ML/LLM Ops, model monitoring, evaluation, and production performance management
- Strong understanding of database systems, data structures, and data processing techniques
- Experience ingesting and integrating data from manufacturing systems (MES, LIMS, CMMS, WMS, ERP)
- Familiarity with OPC-UA and MQTT and industrial automation protocols
- Experience in a manufacturing or industrial environment
- Strong communication and interpersonal skills; ability to tell a story with data
- Adaptability to fast-paced, dynamic environments
- Meticulous attention to detail ensuring data accuracy and high-quality deliverables
Constellation Brands Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Constellation Brands and has not been reviewed or approved by Constellation Brands.
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Healthcare Strength — Healthcare coverage is described as comprehensive, spanning medical, dental, and vision offerings alongside wellness resources. Additional supports such as telemedicine and mental-health programs are positioned as part of the overall package.
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Retirement Support — Retirement benefits appear comparatively strong, with a 401(k) match structure and an added non-elective contribution described in the materials. Profit sharing and employee stock purchase access are also included in the broader financial-security toolkit.
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Leave & Time Off Breadth — Paid time off is framed as generous, covering vacation, holidays, and sick time, with some roles citing substantial starting PTO. Work–life supports such as flexible or hybrid arrangements and summer hours are also part of the offering for eligible roles.
Constellation Brands Insights
What We Do
Constellation Brands (NYSE: STZ) is a leading international producer and marketer of beer, wine, and spirits with operations in the U.S., Mexico, New Zealand, and Italy. Our mission is to build brands that people love because we believe elevating human connections is Worth Reaching For. It’s worth our dedication, hard work, and calculated risks to anticipate market trends and deliver more for our consumers, shareholders, employees, and industry. This dedication is what has driven us to become one of the fastest-growing, large CPG companies in the U.S. at retail, and it drives our pursuit to deliver what’s next. Every day, people reach for our high-end, iconic imported beer brands such as those in the Corona brand family like the flagship Corona Extra, Modelo Especial and the flavorful lineup of Modelo Cheladas, Pacifico, and Victoria; our fine wine and craft spirits brands, including The Prisoner Wine Company, Robert Mondavi Winery, Casa Noble Tequila, and High West Whiskey; and our premium wine brands such as Kim Crawford and Meiomi. As an agriculture-based company, we have a long history of operating sustainably and responsibly. Our ESG strategy is embedded into our business and our work focuses on serving as good stewards of the environment, enhancing social equity within our industry and communities, and promoting responsible beverage alcohol consumption. These commitments ground our aspirations beyond driving the bottom line as we work to create a future that is truly Worth Reaching For. To learn more, visit www.cbrands.com and follow us on Twitter, Instagram, and LinkedIn
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