Analytics Engineer

Choosing Capgemini means choosing a company where you will be empowered to shape your career in the way you'd like, where you'll be supported and inspired by a collaborative community of colleagues around the world, and where you'll be able to reimagine what's possible. Join us and help the world's leading organizations unlock the value of technology and build a more sustainable, more inclusive world.
Your Role
As a Machine Learning Engineer at Capgemini, you will play a critical role in the development, integration, enhancement, and optimization of machine learning solutions that support business decision-making and operational excellence.
You will collaborate closely with data scientists, business stakeholders, and subject matter experts (SMEs) to translate business requirements into scalable technical solutions. This role requires strong Python programming skills, machine learning expertise, cloud experience in Google Cloud Platform (GCP), and the ability to work independently in a fast-paced, data-driven environment.
Responsibilities & Scope
Develop, enhance, and maintain machine learning solutions and predictive analytics models.
Support the integration, deployment, monitoring, and upgrading of ML models in production environments.
Translate business requirements into actionable technical solutions and implementation plans.
Collaborate with SMEs and business stakeholders to understand operational processes and technical requirements.
Develop and optimize data processing workflows using Python, SQL, Pandas, and NumPy.
Build and maintain data visualizations and reporting solutions using Bokeh.
Ensure data quality, reliability, and consistency throughout the machine learning lifecycle.
Manage source code and collaborative development processes using Git.
Participate in testing, validation, and quality assurance activities related to data and machine learning solutions.
Support troubleshooting, performance optimization, and enhancement of deployed analytics applications.
Document technical solutions, development processes, and best practices.
Work effectively both independently and within Agile delivery teams.
Your Profile
Innovation-driven professional – Passionate about data, analytics, and machine learning technologies.
Strong problem solver – Able to break down complex business problems into practical technical solutions.
Independent contributor – Comfortable working with minimal supervision while managing priorities effectively.
Collaborative team player – Works effectively with technical teams, business stakeholders, and domain experts.
Analytical thinker – Skilled at interpreting data and identifying opportunities for optimization.
Continuous learner – Eager to expand expertise in machine learning, cloud, and MLOps technologies.
Qualifications & Preferred Skills
Required Qualifications
Bachelor's Degree in a STEM field (Science, Technology, Engineering, Mathematics, or related discipline).
Experience supporting machine learning projects within enterprise environments.
Advanced English communication skills.
Required Skills
Strong proficiency in Python programming with experience supporting machine learning solutions.
Experience updating, maintaining, and integrating Machine Learning models.
Hands-on experience working with Google Cloud Platform (GCP).
Strong understanding of machine learning concepts and model lifecycle management.
Experience with SQL querying and data analysis.
Proficiency with Pandas and NumPy.
Experience using Git and version control best practices.
Knowledge of software testing and Quality Assurance principles.
Ability to translate business requirements into technical deliverables.
Experience collaborating with Subject Matter Experts (SMEs) and business stakeholders.
Strong analytical, troubleshooting, and communication skills.
Ability to work independently and manage multiple priorities.
Experience building data visualizations using Bokeh.
Preferred Skills
Experience with Data Modeling and ETL processes.
Experience delivering projects using Agile/Scrum methodologies.
Knowledge of Dataiku.
Understanding of performance optimization, monitoring, profiling, and scaling strategies.
Familiarity with signal processing concepts.
Engineering background.
Experience within the Oil & Gas / Oilfield domain, including industry terminology and business processes.
Growth & Development Opportunities
The following areas will be supported through training and enablement programs:
CI/CD Pipelines and DevOps practices.
MLOps and model deployment best practices.
Prognostics & Health Management (PHM) techniques.
Advanced cloud-native machine learning solutions.
Domain-specific analytics and predictive maintenance methodologies.
Job Description
Data engineers are responsible for building reliable and scalable data infrastructure that enables organizations to derive meaningful insights, make data-driven decisions, and unlock the value of their data assets.
Job Description - Grade Specific
The involves leading and managing a team of data engineers, overseeing data engineering projects, ensuring technical excellence, and fostering collaboration with stakeholders. They play a critical role in driving the success of data engineering initiatives and ensuring the delivery of reliable and high quality data solutions to support the organizations data driven objectives.
What You'll Love
Opportunity to work on advanced Machine Learning and AI initiatives with global clients.
Exposure to cloud-native analytics and modern data platforms.
Access to industry-leading training, certifications, and continuous learning programs.
Collaboration with highly skilled data scientists, engineers, and AI specialists.
Innovative and inclusive work environment focused on growth and career development.
Well-being initiatives designed to support your personal and professional success.
Need to Know
Career Development in Spanish & English: Access to certifications, mentorship programs, technical academies, and continuous learning opportunities in both languages.
Community Engagement: Participate in innovation communities, technical events, volunteering initiatives, and knowledge-sharing sessions across Capgemini.
About Capgemini
Capgemini is a global business and technology transformation partner, helping organizations accelerate their dual transition to a digital and sustainable world while creating tangible impact for enterprises and society. It is a responsible and diverse organization with more than 340,000 team members in over 50 countries.
With a strong heritage of more than 55 years, Capgemini helps clients unlock the value of technology through end-to-end services and solutions, leveraging capabilities in strategy and design, engineering, AI, generative AI, cloud, data, and digital transformation.
At Capgemini Mexico, we are committed to fostering a diverse and inclusive workplace where everyone has equal opportunities. We welcome applications from all qualified candidates and evaluate them based on merit, skills, qualifications, and experience relevant to the role.