12 publicaciones de empleo destacadas de machine learning platform engineer en san simón ticumac cdmx (¡Están contratando!)

Research Analyst - Oil Supply
WM de Mexico, S. de R.L. de C.V. —Los Alpes, CDMX
- Tiempo completo
- Microsoft Excel
- Administración de personal
- Inglés
Postulación rápida
Cement Solution Manager
Imubit —Ciudad de México, CDMX
- Home Office (Desde casa)
- Maestría
- Licenciatura
- Sin título de educación superior
9d
Data Scientist Sr 2830
Xideral —Ciudad de México, CDMX
- Home Office (Desde casa)
- Azure
- Doctorado
- Inglés
Postulación rápida
Data Engineer II, DASH Device Operations
Servicios Comerciales Amazon Mexico S. de R.L. de C.V. —Ciudad de México, CDMX
- Tiempo completo
- Informática
- Preparación de alimentos
- Java
Data Scientist (Científico de Datos) - Hybrid
Clara —Ciudad de México, CDMX
- Administración de personal
- Inglés
- SQL
9d
QA Automation Engineer (API & Database Validation)
Nexaminds —Ciudad de México, CDMX
- Home Office (Desde casa)
- Azure
- Administración de personal
- DevOps
Postulación rápida
Senior AI Engineer
Ingersoll Rand —Ciudad de México, CDMX
- Microsoft Excel
- Informática
- Maestría
Staff Data Engineer
Levi Strauss & Co. —Centro (Área 1), CDMX
- Tiempo completo
- Azure
- Informática
- DevOps
Postulación rápida
1d
Practice Lead
Palo Alto Networks —Ciudad de México, CDMX
- Azure
- Liderazgo
Data Engineer Senior with GCP and Python - MX-Any City
Globant —Ciudad de México, CDMX
- Oracle
- DevOps
- SQL
9d
AI DevOps Engineer
Ingersoll Rand —Ciudad de México, CDMX
- Microsoft Excel
- Azure
- Informática
Data Architect / Engineer
Appnovation Technologies —Ciudad de México, CDMX
- Home Office (Desde casa)
- Informática
- SQL
- Licenciatura
Postulación rápida
9d

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Research Analyst - Oil Supply

WM de Mexico, S. de R.L. de C.V. -
Los Alpes, CDMX

Postulación rápida

Información del empleo

Tiempo completo

Cualificaciones

Microsoft Excel
Administración de personal
Visual Basic
Tooling
Bases de datos relacionales
Inglés
Experiencia en bases de datos
SQL
Capacitación
Estimación y pronóstico
VBA
Recolección de datos
Python
Debugging

Descripción completa del empleo

Wood Mackenzie is the global leader in analytics, insights and proprietary data across the entire energy and natural resources landscape.

For over 50 years our work has guided the decisions of the world’s most influential energy producers, utilities companies, financial institutions and governments.

Now, with the world’s energy system more complex and interconnected than ever before, sector-specific views are no longer enough. That’s why we’ve redefined what’s possible with Intelligence Connected.

By fusing our unparalleled proprietary data with the sharpest analytical minds, all supercharged by Synoptic AI, we deliver a clear, interconnected view of the entire value chain. Our trusted team of 2,700 experts across 30 countries breaks siloes and connects industries, markets and regions across the globe.

This empowers our customers to identify risk sooner, spot opportunities faster and recalibrate strategy with confidence – whether planning days, weeks, months or decades ahead.

Wood Mackenzie
Intelligence Connected

WoodMac.com

Wood Mackenzie Brand Video

Wood Mackenzie Values

Inclusive – we succeed together
Trusting – we choose to trust each other
Customer committed – we put customers at the heart of our decisions
Future Focused – we accelerate change
Curious – we turn knowledge into action

Role Purpose

Wood Mackenzie is a leading provider of data, analytics and insights for the energy, chemicals, metals and mining sectors. We help companies, financial institutions and governments make better strategic decisions by combining industry expertise, proprietary data and advanced analytical capabilities.

Within this context, the Oil Supply Team delivers market-leading research, forecasts and data products that help clients understand oil market dynamics and navigate an evolving energy landscape. This role offers the opportunity to contribute to both our research and technical capabilities, supporting the analysis, data infrastructure, models and tools that underpin our products and client solutions. Working closely with analysts, modellers and product teams, you will help ensure our research remains accurate, scalable and impactful while supporting the continued development of our analytical and technology platforms.

Main Responsibilities

We are looking for an Analyst to join our Global Analyst Team within the Oil Supply Team. This role combines industry research and market analysis with technical ownership of key data, modelling and automation workflows that underpin our research products. The successful candidate will be expected to:

Analyse asset, market and industry developments across the commodities and markets they cover, generating short- and long-term forecasts.

Gather, validate and interpret industry data to support Wood Mackenzie's market-leading research and analytical products.

Connect and build relationships with clients and industry participants to inform analysis and strengthen market understanding.

Collaborate with colleagues across Energy and Natural Resources to develop integrated market views and insights.

Produce high-quality written analysis on industry developments, including topics such as the Energy Transition, oil-petrochemical integration and sustainability.

Contribute to client-facing presentations, discussions and research outputs.

During the first six months, the successful candidate will focus on understanding, stabilising and improving the team's existing technical infrastructure by:

Building a thorough understanding of the team's existing data sources, databases, models, tools and workflows, including legacy Python and VBA-based processes.

Identifying inefficiencies, manual processes and points of fragility within existing data pipelines and analytical workflows.

Refactoring and improving legacy codebases to create cleaner, more maintainable and better-documented solutions.

Automating recurring data collection, transformation and update processes to reduce manual intervention and improve reliability.

Documenting key data flows, business logic and technical processes to improve transparency and reduce key-person dependency.

Over time, the role will evolve to include:

Designing, building and maintaining scalable data pipelines, tools and supporting data architecture.

Developing new functionality and services to support the Oil Supply Tool, Macro Oils products and Short-Term Oil Price forecasting models.

Working closely with analysts, modellers and data scientists to improve analytical workflows and model performance.

Applying AI, machine learning and modern data tooling to enhance data processing, modelling workflows and team productivity.

Maintaining and enhancing existing tools and systems to ensure they remain robust, scalable and well-documented.

Collaborating with colleagues across the Macro Oils team to establish data standards, technology best practices and development frameworks.

Supporting continuous improvement initiatives across research, modelling and operational processes.

About You

You are an economist, engineer, geologist, petroleum engineer, data scientist or similar quantitative professional with a strong interest in commodity markets and energy systems. You combine analytical curiosity with strong technical capabilities and enjoy solving complex data and process challenges.

Essential Skills & Experience

Strong analytical and quantitative capabilities, developed through academic study and/or professional experience.

Advanced Python skills, including the ability to develop, debug, maintain and improve production-quality analytical code.

Experience working with large datasets and building data-driven solutions.

Ability to identify opportunities for automation and process improvement.

Strong data management, data quality and troubleshooting skills.

Experience working with Excel, including complex analytical models and data workflows.

Ability to communicate technical concepts clearly to both technical and non-technical audiences.

Excellent written and verbal English communication skills.

Ability to work independently while collaborating effectively across geographically dispersed teams.

Desirable Skills & Experience

Experience with machine learning, AI tools and data science techniques.

Experience with SQL, relational databases and cloud-based data platforms.

Experience maintaining or migrating legacy systems, including VBA-based processes.

Knowledge of oil markets, energy markets or broader commodity sectors.

Background in economics, petroleum engineering, geology, energy systems, data science or a related discipline.

Experience working with forecasting models or decision-support tools.

Expectations

Growth mindset - taking the initiative to learn new skills, seeking out feedback and coaching, and actively applying what has been learned in the workplace.

Change agility - maintaining high performance through disruption and change.

We are a hybrid working company and the successful applicant will be expected to be physically present in the office at least 2 days per week to foster and contribute to a collaborative environment, but this may be subject to change in the future.

This is a full-time role expected to work early mornings to accommodate collaboration with Europe time-zones.

Equal Opportunities

We are an equal opportunities employer. This means we are committed to recruiting the best people regardless of their race, colour, religion, age, sex (including pregnancy, sexual orientation, and gender identity), national origin, disability or protected veteran status. You can find out more about your rights under the law at www.eeoc.gov

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machine learning platform engineer empleos en san simón ticumac cdmx

Research Analyst - Oil Supply

Cement Solution Manager

Data Scientist Sr 2830

Data Engineer II, DASH Device Operations

Data Scientist (Científico de Datos) - Hybrid

QA Automation Engineer (API & Database Validation)

Senior AI Engineer

Staff Data Engineer

Practice Lead

Data Engineer Senior with GCP and Python - MX-Any City

AI DevOps Engineer

Data Architect / Engineer

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