Aboitiz Data Innovation (ADI) is one of the leading up and coming start-ups in the field of Data Science and Artificial Intelligence. We believe data can drive change for a better world by advancing businesses across industries and communities.

We are seeking a highly skilled and motivated Data Scientist to join our team in the industrial and power generation sector. This role requires a strong analytical mind, independent thinking, and a collaborative approach to problem-solving. The ideal candidate will have a deep understanding of data science, machine learning, and computational modeling, along with industry-specific knowledge in physics, material science, and engineering systems.

The successful candidate will work with a wide range of stakeholders, including engineers, operations managers, maintenance teams, and business strategists, to develop data-driven solutions that enhance efficiency, reliability, and predictive maintenance of power generation assets.

Responsibilities

Data Analysis and Modeling:

• Develop and apply advanced statistical, machine learning, and optimization models to analyze large datasets from industrial and power generation systems.
• Identify patterns, trends, and anomalies in data to improve operational efficiency, predict equipment failures, and optimize energy consumption.

Predictive Maintenance:

• Design and implement predictive maintenance models to reduce downtime and extend the lifespan of critical equipment.
• Collaborate with engineering teams to integrate predictive analytics into maintenance workflows.

Process Optimization:

• Use data-driven approaches to optimize industrial processes, such as production lines, energy generation, and resource allocation.
• Apply simulation and optimization techniques to improve system performance and reduce costs.

Stakeholder Collaboration:

• Work closely with cross-functional teams to understand business needs and translate them into data science solutions.
• Communicate complex analytical findings to non-technical stakeholders in a clear and actionable manner.

Data Infrastructure and Tools:

• Develop and maintain scalable data pipelines and workflows to support analytics and modeling efforts.
• Evaluate and implement new tools, frameworks, and technologies to enhance data science capabilities.

Research and Innovation:

• Stay up-to-date with the latest advancements in data science, industrial IoT, and power generation technologies.
• Explore innovative applications of AI/ML in areas such as renewable energy integration, grid stability, and material science.

Requirements

Technical Skills

• Strong programming skills in Python (NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch) and SQL.
• Experience with big data frameworks (Apache Spark, Hadoop) and cloud platforms (AWS, Azure, GCP).
• Expertise in machine learning, deep learning, and reinforcement learning.
• Proficiency in time-series forecasting techniques (ARIMA, LSTMs, Prophet) for power system analytics.
• Knowledge of Bayesian statistics and probabilistic modeling.
• Familiarity with physics-informed machine learning and computational simulations.
• Experience with graph analytics and network modeling for power grid analysis.
• Strong grasp of data visualization tools (Tableau, Power BI, Plotly, Matplotlib, Seaborn).
• Understanding of SCADA systems, industrial automation protocols, and sensor networks is a plus.

Soft Skills

• Strong problem-solving abilities and critical thinking skills.
• Excellent communication skills, with the ability to explain complex models to non-technical stakeholders.
• Ability to work independently and collaboratively in a fast-paced environment.
• Proactive in learning and keeping up with emerging technologies in the industrial AI space.

Preferred Qualifications:

• Bachelor's degree (minimum) in Data Science, Computer Science, Engineering, Physics, Material Science, or a related field.
• Open to fresh graduates with strong technical experience and a portfolio of projects demonstrating expertise in data science and machine learning.
• Master’s or Ph.D. in a relevant field is considered a plus.
• Experience in the power generation sector, renewable energy analytics, or industrial maintenance.
• Background in numerical modeling (Finite Element Analysis, Computational Fluid Dynamics).
• Exposure to Digital Twins and Industrial AI applications.
• Hands-on experience with AI-driven process optimization and control systems.

Please refer to job description.