Operational Data Intelligence Specialist

H+K INTERNATIONAL; San Luis Potosí; On-site; MXN 600,000 - 900,000; Full time

Job summary

H+K INTERNATIONAL seeks an AI & Operational Data Intelligence Specialist to transform operational data into automated, actionable intelligence across manufacturing, quality, supply chain, and logistics. You will design dashboards, build predictive analytics, and deploy AI solutions to improve visibility, productivity, and cost efficiency.

The role requires strong data engineering, BI, and ML skills with a focus on governance and user enablement.

Qualifications

• Bachelor’s degree in data science, AI, software engineering, industrial engineering, mechatronics, IT, applied mathematics or related field.
• Master’s degree in data science, AI, analytics or similar is desirable but not required.

Responsibilities

• Data Automation & Integration: Automate data extraction, cleansing, transformation, and consolidation from multiple operational systems.
• Business Intelligence & Operational Analytics: Design and develop automated dashboards for Production, Quality, Logistics, Planning, Engineering, and Management; develop KPI monitoring systems and scorecards.
• Artificial Intelligence & Predictive Analytics: Identify opportunities to apply AI/ML; develop predictive models for capacity, downtime, inventory, delivery, and process deviations; implement anomaly detection and early-warning systems.
• Real‑Time Operational Intelligence: Develop real-time or near-real-time performance monitoring; create automated alerts for KPIs; support proactive decision-making.
• Data Governance: Establish data quality standards, ownership, validation, and traceability; document sources, transformations, calculations, and business rules.
• User Enablement & AI Adoption: Train users on BI, analytics, automation, and AI tools; promote data-driven decision-making; identify repetitive activities to automate using AI.

Skills

Strong analytical

Problem-solving

Autonomy

Stakeholder communication

Education

Bachelor's degree in Data Science

Bachelor's degree in Artificial Intelligence

Bachelor's degree in Software Engineering

Master’s degree in data science/AI/Analytics

Mechatronics/Industrial Engineering

Applied Mathematics

Information Technology

Tools

Python

SQL

Power BI

Advanced Excel

Data modeling

ETL/ELT

APIs

Power Query

Power Automate

Git

Microsoft Fabric/Azure

Databricks

Snowflake

MLflow

Scikit-learn

TensorFlow/PyTorch

OpenAI/Azure OpenAI APIs

LLMs/Generative AI

RAG architectures

Copilot ecosystem

ERP/MES integration

Job description

AI & Operational Data Intelligence Specialist

Position Objective

Transform operational data into automated, reliable, and actionable intelligence to accelerate decision‑making across Manufacturing, Quality, Supply Chain, Logistics, Planning, and Engineering.

The position will be responsible for developing and implementing data automation, Business Intelligence, Artificial Intelligence, and predictive analytics solutions that improve operational visibility, productivity, quality, cost, and overall business performance.

Key Responsibilities.

1. Data Automation & Integration
   • Automate data extraction, cleansing, transformation, and consolidation from multiple operational systems.
   • Integrate information from ERP, MES, production systems, quality databases, Excel files, SQL databases, APIs, and other operational sources.
   • Reduce manual data manipulation and reporting activities.
2. Business Intelligence & Operational Analytics.
   • Design and develop automated dashboards for Production, Quality, Logistics, Planning, Engineering, and Management.
   • Develop KPI monitoring systems and management scorecards.
   • Implement automated reporting and exception‑based notifications.
   • Transform operational data into actionable insights for management.
3. Artificial Intelligence & Predictive Analytics
   • Identify opportunities to apply AI and Machine Learning to manufacturing and business processes.
   • Develop predictive models for areas such as:
   • Capacity and demand
   • Downtime
   • Inventory
   • Delivery performance
   • Process deviations
   • Implement anomaly detection and early‑warning systems.
   • Evaluate and implement Generative AI and LLM‑based solutions where they provide measurable business value.
4. Real‑Time Operational Intelligence
   • Develop solutions for real‑time or near‑real‑time performance monitoring.
   • Create automated alerts when KPIs exceed defined thresholds.
   • Support management with proactive rather than reactive decision‑making.
5. Data Governance
   • Establish standards for data quality, ownership, validation, and traceability.
   • Develop a reliable “single source of truth” for key operational KPIs.
   • Document data sources, transformations, calculations, and business rules.
6. User Enablement & AI Adoption
   • Train operational and management users on BI, analytics, automation, and AI tools.
   • Promote data‑driven decision‑making across the organization.
   • Identify repetitive analytical and administrative activities that can be automated using AI.

Education

Bachelor’s degree in:

• Data Science
• Artificial Intelligence
• Software Engineering
• Industrial Engineering
• Mechatronics
• Information Technology
• Applied Mathematics

or related field.

Master’s degree in data science, AI, Analytics, or similar fields is desirable but not required.

Experience

Preferred: 2–4 years of professional experience, including:

• Data Analytics / Business Intelligence
• Data Engineering
• Process automation
• Manufacturing or operational analytics
• AI / Machine Learning implementation

Technical Skills

Required

• Python
• SQL
• Power BI
• Advanced Excel
• Data modeling
• ETL / ELT
• APIs
• Power Query
• Power Automate
• Git

Preferred

• Microsoft Fabric / Azure
• Databricks
• Snowflake
• MLflow
• Scikit-learn
• TensorFlow / PyTorch
• OpenAI / Azure OpenAI APIs
• LLMs and Generative AI
• RAG architectures
• Microsoft Copilot ecosystem
• ERP / MES integration

Competencies

• Strong analytical and structured thinking
• Problem-solving
• Business-oriented mindset
• Ability to translate operational problems into digital solutions
• High degree of autonomy
• Communication with both technical and non‑technical stakeholders
• Continuous improvement mindset
• Project management
• Ability to prioritize projects based on business impact

Languages

• Spanish: Native / Advanced
• English: Advanced business and technical communication