AI/ML Scientist

Nasze wymagania:
Bachelor’s or advanced degree in Data Science, Statistics, Computer Science, Engineering, Applied Mathematics, Operations Research, or related field.
Strong proficiency in Python, including experience with scientific and machine learning libraries such as scikit-learn, TensorFlow, PyTorch, XGBoost, SciPy, Matplotlib, and related tools.
Solid understanding of machine learning and statistical modeling concepts, including time-series analysis, feature engineering, optimization, experimentation, and model evaluation techniques.
Experience applying advanced analytics, AI, and machine learning techniques within mining and metals, energy, infrastructure, manufacturing, or other asset-intensive industrial sectors. Experience with computer vision, Vision AI, and LLM/LVM applications is considered a strong asset.
Experience working with industrial-scale datasets, including process historian data, sensor data, operational datasets, and time-series data.
Working knowledge of data engineering and MLOps concepts, including SQL, APIs, ETL/ELT workflows, cloud platforms (Azure, AWS, or GCP), and model deployment practices.
Strong communication and collaboration skills, with the ability to work effectively across multidisciplinary teams and rapidly learn and apply new technologies and concepts.
Ability to frame ambiguous business challenges into structured analytical approaches, and communicate complex technical findings effectively to technical and non-technical audiences.
The following experience and skills are considered strong assets:
Familiarity with industrial IT/OT environments, including data historians (e.g., AVEVA PI System), real-time data integration, control systems, instrumentation, P&IDs, and industrial cybersecurity considerations.
Experience with mathematical optimization techniques and tools, such as CPLEX, Gurobi, FICO Xpress, or similar optimization frameworks.
Experience operationalizing AI/ML solutions using modern data platforms and MLOps practices (e.g., Databricks, MLflow, CI/CD pipelines, model monitoring, and lifecycle management).
English level C1

Mile widziane:
Spanish language

Zakres obowiązków:
Model Development and Deployment:
Design, develop, validate, and deploy AI/ML models for industrial applications, including predictive maintenance, process optimization, anomaly detection, forecasting, computer vision, and prescriptive analytics.
Apply advanced AI and machine learning methodologies, including supervised and unsupervised learning, deep learning, reinforcement learning, optimization techniques, and large language models (LLMs), where appropriate, to solve complex industrial challenges.
Develop robust data pipelines, feature engineering workflows, and analytical frameworks to transform raw operational and process data into actionable insights and production-ready solutions.
Translate complex analytical findings into practical recommendations aligned with operational goals and business objectives.
Collaborate closely with process engineers, data engineers, control specialists, and IT/OT teams to deploy AI and machine learning solutions into production environments and integrate models with enterprise systems, operational platforms, dashboards, and decision-support tools.
Delivery Excellence and Technology Development:
Partner with clients and internal teams to identify high-value AI opportunities and quantify business impact and value potential.
Conduct data-driven opportunity assessments, proof-of-value (PoV) studies, and rapid prototyping initiatives to demonstrate measurable business outcomes and communicate insights effectively to internal and external stakeholders.
Support the end-to-end AI lifecycle, from problem definition and data exploration through model development, validation, deployment, monitoring, and continuous improvement.
Contribute to the growth of Hatch’s AI and advanced analytics capabilities through the development of reusable frameworks, accelerators, methodologies, and best practices.
Stay current with emerging trends and technologies in artificial intelligence, machine learning, optimization, and industrial analytics, bringing innovative approaches to client challenges.
Contribute to technical publications, conference presentations, white papers, and internal knowledge-sharing initiatives.

Oferujemy:
Flexible work environment
Long term career development
Think globally, work locally