Gather, analyze and interpret data from various sources that will suggest conclusions and support decision-making in prostate cancer risk outcomes. Manage data: inspect, clean, and transform data. Run database queries and provide datasets to project team members. Apply the best available machine learning techniques to the task of drawing inference from data. Prepare, present and publish reports and findings in research conferences, seminars and journals.

Daily Operations

• Work with large scale multimodal datasets to extract insights.
• Gather, analyze and interpret data from various sources that will suggest conclusions and support decision-making in prostate cancer risk outcomes.
• Apply the best available techniques to the task of drawing inference from data.
• Manage data: inspect, clean, and transform data. Run database queries and provide datasets to project team members.
• Maintain large data sets: merge files, restructure and recode variables, assign labels and values, check for errors, create codebooks, etc.
• Develop, streamline, error-proof, and automate processes for managing data and producing reports.
• Prepare, present and publish reports and findings in research conferences, seminars and journals.

Required Skills

• A bachelor’s/master’s degree in computer science, data science, statistics, biomedical informatics, econometrics, or a recognized field of science directly related to the data science tasks required for this position.
• Experience using programming languages (R, Python, SQL, etc.) to manipulate data and draw insights from large data sets.
• Experience working with and creating data architectures.
• Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.
• Knowledge of a variety of deep learning techniques (convolutional neural networks, deep neural networks, transfer learning, generative adversial neural networks etc.) and their real-world advantages/drawbacks.
• Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications.
• Excellent written and verbal communication skills for coordinating across teams.
• A drive to learn and master new technologies and techniques.

Preferred Skills

• Experience with Python programming language
• Experience with data visualizations for a non-technical audience.
• Experience with developing and applying machine learning techniques on variety of data
• Experience working with statistical exploration and techniques to generate data insights