Data Scientist - AI/ML for Manufacturing & IoT (LATAM, English Required)

AI overview

Contribute to innovative AI and machine learning projects in manufacturing, working with diverse teams on high-impact use cases and delivering actionable insights from complex data.

Work at DaCodes!
We are a high-impact software and digital transformation firm.
For over 10 years, we have been creating technology- and innovation-driven solutions thanks to our team of more than 300 talented #DaCoders, including developers, architects, UX/UI designers, PMs, QA testers, and more. Our team collaborates on projects with clients across LATAM and the United States, consistently delivering outstanding results.
At DaCodes, you will have the opportunity to accelerate your professional growth, work on diverse projects across multiple industries, and contribute to the design, implementation, and optimization of cloud-based infrastructures.
Our DaCoders play a key role in the success of our business and our clients’ businesses. You will be the expert contributing to our projects and will have access to disruptive startups and global brands.
Interested?

We are looking for a Data Scientist with strong experience applying AI, Machine Learning, and Data Science in manufacturing and industrial environments, including IoT, robotics, and embedded systems. In this role, you will collaborate closely with manufacturing, operations, and business teams to identify high-impact AI/ML opportunities and lead end-to-end machine learning initiatives that deliver real business value.

Requirements

Key responsibilities:

  • Collaborate with manufacturing, operations, and business stakeholders to identify, groom, and prioritize AI/ML use cases, defining project scope, objectives, and success metrics.
  • Own end-to-end machine learning projects, including data collection, data preparation, feature engineering, model development, deployment, and ongoing monitoring in production environments.
  • Analyze large-scale manufacturing data from MES, ERP, and IoT sensor sources to uncover insights and optimization opportunities.
  • Build predictive and prescriptive models for use cases such as quality improvement, predictive maintenance, process optimization, and operational efficiency.
  • Develop and maintain data pipelines and analytical workflows using Python and SQL.
  • Write clean, efficient, and maintainable code to support scalable AI/ML solutions.
  • Translate complex analytical results into clear, actionable insights for non-technical stakeholders and decision-makers.

Desired profile:

  • 3+ years of experience in Data Science, Machine Learning, or AI, with strong overall professional experience.
  • Proven experience in manufacturing or industrial environments (IoT, robotics, embedded systems).
  • Strong analytical thinking and problem-solving skills.
  • Excellent communication and collaboration abilities, capable of working with cross-functional and multicultural teams.

Tools & technologies:

  • Advanced proficiency in Python and machine learning libraries such as scikit-learn, TensorFlow, and PyTorch.
  • Strong SQL skills for data extraction, querying, and manipulation.
  • Experience with data visualization tools such as Power BI or Tableau.
  • Basic understanding of MLOps concepts, including model deployment, versioning, and monitoring.
  • Experience working with time-series data and sensor-generated datasets.

Additional requirements:

  • Advanced English required for collaboration with international teams.
  • Position open to LATAM, including Mexico.
  • Remote work availability and flexibility to collaborate across time zones.

Nice to have:

  • Experience with cloud platforms such as AWS, Azure, or GCP.
  • Knowledge of time-series analysis, anomaly detection, or optimization techniques.
  • Understanding of manufacturing processes, data sources (MES, ERP), and common challenges such as quality control, predictive maintenance, and order backlog management.

Benefits

🚀 Integration with global brands and disruptive startups.

🏡 Remote work / Home office.

📍 If a hybrid or on-site modality is required, you will be informed from the first interview.

⏳ Work schedule aligned with the assigned project or team.

📅 Monday to Friday work schedule.

🎉 Day off on your birthday.

🏥 Major medical insurance (applies to Mexico).

🛡️ Life insurance (applies to Mexico).

🌎 Multicultural work teams.

🎓 Access to courses and certifications.

📢 Meetups with special guests from the IT industry.

📡 Virtual integration events and interest groups.

📢 English classes.

🏆 Opportunities within our different business lines.

🏅 Proudly certified as a Great Place to Work.

Perks & Benefits Extracted with AI

  • Education Stipend: Access to courses and certifications.
  • Health Insurance: Major medical insurance (applies to Mexico).
  • Birthday day off: Day off on your birthday.
  • Remote-Friendly: Remote work / Home office.

¡Trabaja en DaCodes!Somos una firma de expertos en software y transformación digital de alto impacto, líderes en la península maya. Por más de 6 años hemos creado soluciones enfocadas en la tecnología e innovación gracias a nuestro equipo de +100 talentosos #DaCoders, arquitectos, diseñadores UIUX, PMs, QA testers y más, que se integran a nuestros proyectos para lograr resultados sobresalientes.Buscamos impulsar y acelerar tu desarrollo profesional al colaborar en diversidad de proyectos, sectores y giros empresariales. Trabajar en DaCodes te permitirá ser versátil y ágil al poder trabajar con diversas tecnologías y colaborar con profesionales de alto nivel.Nuestros DaCoders tienen gran impacto en el éxito de nuestro negocio, así como en el éxito de nuestros clientes. Serás el experto que participará en nuestros proyectos y tendrás acceso a startups disruptivas y marcas globales;¿Te pareció interesante?¡Estamos en busca de talento para unirse al equipo, vamos a trabajar juntos!El candidato o candidata ideal tiene una combinación única de experiencia técnica, curiosidad, mentalidad lógica y analítica, proactividad, ownership, y gusto por el trabajo en equipo

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