Overview:
We are looking for a Data Scientist to join our team on-site with the NaphCare Charitable Foundation located in Birmingham, AL 35216. The data scientist will join a team of engineers, researchers and product owners to deliver innovative, automated, and technologically advanced healthcare solutions through the integration of predictive models and analytical insight.
US Citizen or Green Card only. Candidates local to Birmingham preferred.
As a Data Scientist at the NaphCare Charitable Foundation, you will work with advanced hardware, software, and techniques to develop computational algorithms and statistical methods that find patterns and relationships in large volumes of healthcare data. The core contributions of the Data Scientist will consist of collaborating with a multi-disciplinary team, defining experimentation setups, researching data-driven solutions to the problems identified, providing technical mentorship to other team members, and communicating results to stakeholders.

Responsibilities:

• Serve as a technical mentor to the team. Encourage and set the example for collaboration across functional areas and disciplines.
• Design and implement metrics, pipelines and tools that will enable engineers to achieve their data insights.
• Make strategic recommendations on data collection, integration and retention incorporating business requirements and knowledge of best practices.
• Keep up to date on related technologies and frameworks, and propose new ones that the team could leverage.
• Work with large, complex data sets. Solve difficult, non-routine analysis problems, applying advanced analytical methods as needed. Conduct analysis that includes data gathering and requirements specification, processing, analysis, ongoing deliverables, and presentations.
• Summarize and clearly communicate data analysis assumptions and results
• Identify shifts, determine new ways of looking at data, and creatively drive improvements in products.
• Build and prototype analysis pipelines to iteratively test hypothesis.
• Interact cross-functionally, making business recommendations to stakeholders.

Qualifications:

• Proven excellence in leading and contributing to Data Science projects.
• Proven track record of pushing state of the art in the data science / machine learning space.
• Strong communication, interpersonal skills and the fortitude to accomplish your goals.
• Experience in leading discovery with stakeholders to identify requirements and the expected outcomes.
• Capability to educate the organization both from technical and the business perspectives on new approaches, such as testing hypotheses and statistical validation of results.
• Demonstrate the following scientist qualities: clarity, accuracy, precision, relevance, depth, breadth, logic, significance, fairness and aptitude for original research.
• Comfortable working in a team environment.
• Expert level in machine learning architecture and model development.
• Strong working knowledge of statistical frameworks (Pandas, NumPy/SciPy, scikit-learn) (3+ years)
• Strong working knowledge of machine learning frameworks (PyTorch, TensorFlow) (3+ years)
• Mastery in building SQL queries
• Experience monitoring the full life cycle of models
• Experience with ETL pipelines
• Strong verbal and written communication skills
• Strong problem-solving skills to help refine problem statements and figure out how to solve them with the available data
• Curious and driven to solve complex problems
• Smart but humble, action oriented

PREFERRED QUALIFICATIONS:

• Experience with distributed processing technologies
• Experience with human-in-the-loop machine learning solutions
• Medical Industry experience

REQUIRED EDUCATION

Ph.D. or MS in the fields of Engineering, Analytics, Mathematics, Computer Science, Statistics, Machine Learning, or other quantitative fields

• Serve as a technical mentor to the team. Encourage and set the example for collaboration across functional areas and disciplines.
• Design and implement metrics, pipelines and tools that will enable engineers to achieve their data insights.
• Make strategic recommendations on data collection, integration and retention incorporating business requirements and knowledge of best practices.
• Keep up to date on related technologies and frameworks, and propose new ones that the team could leverage.
• Work with large, complex data sets. Solve difficult, non-routine analysis problems, applying advanced analytical methods as needed. Conduct analysis that includes data gathering and requirements specification, processing, analysis, ongoing deliverables, and presentations.
• Summarize and clearly communicate data analysis assumptions and results
• Identify shifts, determine new ways of looking at data, and creatively drive improvements in products.
• Build and prototype analysis pipelines to iteratively test hypothesis.
• Interact cross-functionally, making business recommendations to stakeholders