| Senior ML Scientist at Remote, Remote, USA |
| Email: [email protected] |
| Title: Senior ML Scientist Location: Remote Client : CITIUS TECH If you are interested, please share your updated resume Job Description Job Description: The ideal candidate will have deep expertise in time-series data processing, as well as hands on experience with structured and unstructured data processing pipelines, and a solid background in statistics and machine learning/deep learning algorithms. In this role, you will develop, implement, and optimize machine learning and deep learning models tailored to complex multi-modal datasets. You will work closely with cross-functional teams, including AI leads, ML engineers, and product owners, to develop cutting-edge solutions that impact millions of lives worldwide. The Senior ML Scientist will directly report to the Head of AI. Responsibilities: Design and develop machine learning models for time-series analysis, structured and unstructured data processing, and predictive analytics. Create and implement data preprocessing pipelines for various data types, including time-series, structured (e.g., tabular), and unstructured (e.g., text, images). Apply statistical techniques and feature engineering to optimize data representations for modeling. Train, fine-tune, and evaluate machine learning and deep learning models, ensuring high accuracy, robustness, and scalability. Stay up-to-date with the latest advancements in machine learning, deep learning, and time-series modeling, integrating innovative approaches into projects. Work closely with data scientists, software engineers, product managers, and clinical experts to align on project requirements and ensure successful model deployment. Prepare technical documentation, research papers, and presentations to communicate findings and results to both technical and non-technical audiences. Qualifications: Ph.D. or Master s degree in Computer Science, Statistics, Data Science, or a related field with a focus on machine learning and data science. Minimum of 5 years of hands-on experience in machine learning, with a focus on time-series analysis, structured, and unstructured data processing. Proficiency in Python and libraries such as Pandas, NumPy, Scikit-Learn. Experience with deep learning frameworks such as TensorFlow or PyTorch. Strong understanding of time-series forecasting techniques, signal processing, and traditional statistical methods. Experience with handling unstructured (e.g., text, images) and structured data sources. Knowledge of feature engineering, model evaluation, and model interpretability. Strong analytical and problem-solving skills. Excellent communication skills, both written and verbal. Ability to work in a fast-paced, collaborative environment with cross-functional teams. Experience with healthcare or clinical data is a plus. Keywords: artificial intelligence machine learning |
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| Thu Nov 07 22:49:00 UTC 2024 |