Data Analytics & Simulation Professional
The Data Analytics Team within Siemens Healthineers is looking for data scientists with a background in machine learning (ML) and deep learning (DL) technologies to help design and build innovative AI solutions and products for the SPECT/PET scanners. The successful candidate will be part of a team, building cutting-edge AI solutions that rely on AI and ML techniques including but not limited to computer vision, deep learning, natural language processing, and machine learning.
• Bridge industry and research, keeping the team focused on high-value problems at the cutting edge of emerging trends.
• Ability to communicate complex black-box models to cross-functional stakeholders.
• Be very strong in algorithms, data structures, problem-solving, building to scale by leveraging cloud computing.
• High sense of ownership.
• Deep machine learning models, using a deep graph with multiple processing layers & composed of multiple linear and non-linear models/techniques.
• Implemented advanced techniques for outlier and anomaly detection including applications of clustering & learned rules.
• Advanced knowledge of machine learning algorithms, practical experience of parameter and performance tuning, Dimensionality Reduction, High Dimensionality Modelling, Ensembling, Feature Engineering.
• Data Extraction from EDW/Big Data Platform, Dataset Preparation (creation of base data, aggregation, transformation), performing EDA.
• Strong skills for data wrangling / analysis / visualization / modeling.
• Good Logical / Analytical / Quantitative /Reasoning skills.
• Desire to learn new tools & techniques and follow the latest thinking globally in academia and the business world.
Tools & Technologies
• Strong understanding of SQL language for data management.
• Exposure to Power BI, Tableau, Graph DB, Mongo DB and AWS is an added advantage.
• Knowledge of R or Python Libraries - Scipy, Numpy, Pandas, IPython, Scikit-learn.
• Bachelors, Masters, or Ph.D. degree in computer science, engineering, statistics, or related technical/scientific field.
• 5+ years of professional experience in a business environment.
• 3+ years of relevant experience in building large scale machine learning models and products.
• Exposure to deep learning (e.g., CNN, RNN, LSTM)
• Good knowledge of deep learning hardware and software - GPUs, TPUs and CPUs, TensorFlow, PyTorch, Caffe
• Strong communication and data presentation skills
• Strong attention to detail
• Comfortable working in a fast-paced, highly collaborative, dynamic work environment
• Ability to think creatively and solve problems