Data Scientist - Lewis Katz School of Medicine
About the Role
The ALS Center of Hope at Temple University is seeking an experienced Data Scientist to help organize, integrate, and analyze the complex datasets driving our ALS research program. This role sits at the intersection of clinical neuroscience and modern machine learning, supporting work that ranges from natural history data curation to our gene-by-environment (G×E) studies and the translation of animal genetic modifier findings into human ALS data. The successful candidate will design and maintain scalable machine learning pipelines across on-premises and cloud environments, integrate new data sources as our multi-modal datasets grow, and fine-tune foundation models for research applications. They will also mentor colleagues and help translate emerging methods into practical tools for our team. This is an opportunity to apply cutting-edge data science directly to one of the most challenging problems in neurology, working alongside a collaborative team dedicated to understanding and ultimately defeating ALS.
Responsibilities
- Design, develop, and implement end-to-end machine learning production pipelines for on-premises and cloud-based workflows
- Develop and maintain scalable data pipelines and build out new API integrations to support continuing increases in data volume and complexity
- Fine-tune foundation models and continuously monitor their performance
- Mentor team members and contribute to a collaborative, high-performance development environment
- Apply emerging research to practical use cases, staying current with advancements in machine learning and ALS research
- Perform other duties as assigned
Required Education and Experience
- Bachelor's or Master's degree in Computer Science, Mathematics, Engineering, or related field
- Minimum of 2 years of directly related experience in Data Science, Machine Learning, or related fields
- An equivalent combination of education and experience may be considered
Required Skills and Abilities
- Strong expertise in Python, SQL, and modern ML frameworks (TensorFlow, PyTorch, Scikit-Learn)
- Experience with MLOps tools (MLflow, Kubeflow, Airflow) for model deployment and monitoring
- Proven experience in designing and implementing machine learning solutions at scale on AWS or similar cloud platforms
- Strong understanding of probability theory, statistics, and experimental design
- Experience with staged deployment for both development testing and model segregation
Preferred Qualifications
- 4 years of experience in Data Science, Machine Learning, or related fields
- Experience with HIPAA, IRB, and other healthcare data compliance frameworks
- Hands-on experience in medical research python libraries (e.g., MNE-python, NiBabel, DiPY, etc.)
- Hands-on experience in LLMs (e.g., GPT, BERT, LLaMA, Claude) and Generative AI technologies
- Hands-on experience in Retrieval-Augmented Generation (RAG)
- Experience in creating databases, data warehouses, and data lakes for multi-modal datasets
- Proficiency in business intelligence (BI) tools and data visualization
- Professional cloud certification preferred (i.e. AWS SAA-C03 level or above)
Benefits
- Full medical, dental, vision coverage
- Paid time off
- 11 Paid Holidays
- Tuition remission - eligible employees and their dependents can obtain a degree TUITION FREE
- A generous retirement plan
Pay
Salary Grade: T26. Salary Range: $60,000 to $70,000. A variety of important factors are reviewed by HR when considering salary, including job duties, the applicant's education and experience, all relevant internal equity considerations, department budget, and funding source.
Schedule
This is a hybrid position.