Data Scientist - Philadelphia, United States - NeuroFlow

Description

Job Summary:

The Data Scientist will work closely with our data science, engineering, and product teams to architect and maintain our data stack, from ingestion through stakeholder consumption. This includes adhering to engineering best practices and optimizing for future scalability and maintainability. The Data Scientist will report directly to the SVP of Healthcare Informatics and provide guidance and mentorship in the areas of data science, data architecture, and data modeling to the organization. The Data Scientist will oversee the development of our machine learning pipeline to support operational analytics, including enhancements to our NLP processes and risk stratification algorithms. Additionally, administrate all systems required to support our data infrastructure. These systems include but are not limited to Snowflake, FiveTran, DBT, AWS and AWS SageMaker. This role requires an individual who is adept at the technical aspects of data analysis, industry leading data science methods, and also the project management skills needed to lead strategic initiatives and liaise between departments. This will require an optimistic 'can do' personality with strong communication skills and the ability to meet aggressive project completion timelines.

Key Responsibilities:

• Data Strategy: Execute the department's comprehensive data and analytics strategy that aligns with the company's objectives and the healthcare industry's evolving needs.
• Team Leadership: Manage project and partner and develop data analysts by providing guidance and mentorship.
• Machine learning and Data Analysis: Hands-on experience in a wide range of supervised and unsupervised approaches including classification and multiclassification problems. Also performs analysis of complex data sets to identify trends, patterns, and insights that inform company strategy and decision-making.
• Cross-functional Collaboration: Partner with various departments (e.g., IT, operations, clinical teams) to understand their data and analytics needs and provide support.
• Project Management: Manage multiple analytics projects, ensuring they are delivered on time, within scope, and within budget.
• Innovation and Improvement: Continuously seek out and implement improvements in analytics methods and tools to enhance the team's capabilities and the company's competitive edge.
• Vendor Management: Evaluate and manage relationships with external vendors providing analytics tools or services.
• Compliance and Ethics: Ensure that data management and analysis practices adhere to ethical guidelines and comply with relevant healthcare regulations (e.g., HIPAA).
• Stakeholder Communication: Communicate complex analytical concepts and results to non-technical stakeholders, facilitating data-driven decision-making across the company.

Required Qualifications:

• Bachelor's or Master's degree in Analytics, Statistics, Computer Science, Health Informatics, or a related field.
• Significant experience in data analytics or business intelligence, preferably within the healthcare sector.
• Strong leadership skills with a track record of managing and developing high-performing teams.
• Proficiency in data analytics tools, statistical computing, and data science platforms (e.g., SQL, R, Python, AWS, AWS Sagemaker, Glue) and business intelligence platforms (e.g., Tableau, Power BI).
• Excellent project management skills with the ability to manage timelines, resources, and stakeholder expectations.
• Strong understanding of the healthcare industry, including regulatory and compliance environments.

Preferred Qualifications:

• 4+ years of experience with advanced analytics techniques, such as predictive modeling, and machine learning.
• 3+ years working with medical data for population analysis in the areas of suspect diagnosis, severity stratification, and therapy adherence.
• Knowledge of healthcare data standards (e.g., HL7, FHIR) , medical claims and EHR systems.
• Proven ability to translate analytics into strategic insights that drive successful business outcomes.

Tools and Platforms:

• Experience with the following tools and platforms will be required: SQL, Python, AWS Redshift, AWS Sagemaker , VSCode, Jupyter Notebook, Git , Azure, Pandas, Scikit-learn, tidyr, ggplot2, Tableau, TensorFlow, NumPy, R, SAS, Docker (a plus),