Senior Data Scientist (21888)

At Aker Solutions we are changemakers with nearly 200 years of experience, committed to helping the energy industry #PowerTheChange towards a net-zero future. We are driven by collaboration and curiosity, building tomorrow’s technological solutions today!

We are looking for a SeniorData Scientist to design, build, and deploy advanced machine learning models for industrial applications. The role will focus on transforming complex operational, sensor, production, and process data into reliable predictive and prescriptive solutions that improve efficiency, quality, safety, and decision-making. The ideal candidate has strong experience in applied machine learning, statistical modeling, industrial data, and productiongrade model development. Key Responsibilities • Develop, validate, and deploy advanced deep learning and machine learning models for industrial use cases such as predictive maintenance, process optimization, anomaly detection, quality prediction, demand forecasting, and asset performance monitoring. • Work with large-scale structured, unstructured and time-series data fromindustrial systems, sensors, machines, production lines, and operational platforms. • Collaborate with engineers, domain experts, product teams, and business stakeholders to identify high-value machine learning opportunities. • Translate industrial challenges into data science problems and deliver practical, scalable solutions. • Build robust data pipelines, feature engineering workflows, and model evaluation frameworks. • Monitor model performance in production and support continuous improvement of deployed models. • Communicate model insights, assumptions, limitations, and business impact clearly to technical and non-technical stakeholders.

Masters or PhD in Data Science, Computer Science, Statistics,Mathematics, or a related field • 8+ years of professional experience as a Data Scientist,Machine Learning Engineer, or similar role. • Strong professional experience in deep learning frameworks (TensorFlow, PyTorch). • Proven experience in building machine learning models for real-world, production-oriented use cases. • Strong knowledge of supervised and unsupervised learning, time-series modeling, anomaly detection, optimization, and statistical analysis. • Experience working with industrial, manufacturing, energy, logistics, process, or IoT data. • Proficiency in Python (Pandas, Scikit-learn, NumPy, etc.), SQL, and data visualization tools. • Understanding of MLOps practices, model deployment, monitoring, versioning, and reproducibility. • Experience with predictive maintenance, digital twins, process control, industrial automation, or sensor analytics. • Experience with Azure cloud platform. • Experience with Databricks, Spark, Kubernetes, MLflow, Airflow, or similar tools. • Knowledge of edge deployment or real-time machine learning systems. • Strong communication skills and ability to work across technical and business teams. 1.3 Desired Skills • Industrial machine learning • Time-series forecasting • Predictive maintenance • Anomaly detection • Image classification • Object detection • Feature engineering • Statistical modeling • MLOps • Python • SQL • Cloud platforms • Data pipelines • Model deployment and monitoring