Lead Data Scientist

Sift Healthcare is seeking a Lead Data Scientist to join our highly collaborative, growing analytics group. This hire will work closely with our data science and engineering teams to enhance Sift’s data science, ML Ops, and advanced analytics infrastructure, techniques, and practices.

Sift is transforming healthcare payments by equipping healthcare organizations to fully leverage their payments data to work smarter, protect their margins and accelerate cash flow. Large health systems, leading HCIT vendors, payers and outsourced revenue management agencies use Sift's Payments Intelligence Platform, ML integrations and advanced analytics to optimize payment outcomes and enable data-driven decision-making within the revenue cycle.

The Lead Data Scientist is a key member of the Data Science team, responsible for improving and enhancing Sift’s suite of predictive models and operations that work to solve complex healthcare payment problems. We are seeking a candidate with 5+ years of experience in a machine learning role and an advanced degree (MS or higher) in a related field. The ideal candidate will have some experience with Deep Learning and Generative AI.

A key attribute of the employee will be their ability to test hypotheses and present findings to upper management, both internally and externally, and help other team members do the same. They must be collaborative, have strong communication skills and mentor team members. The employee must develop a deep understanding of the data Sift utilizes, provide advanced analysis, and suggest how Sift Healthcare can improve current ML techniques and infrastructure. The employee is expected to remain up to date with current ML trends.

Experience working with PII/PHI/HIPAA data is required. Experience working with healthcare data is required. A Wisconsin resident is preferred for this role.

RESPONSIBILITIES

• Collaborate and assist in the development of Sift’s current ML products and codebase while building and advancing into the future of deep learning and Generative AI
• Conduct and assist in code reviews, pipeline development, debugging, and versioning best practices
• Work and communicate effectively across teams and with leadership
• Enhance the development of technical solutions to business problems that generalize and scale, with an extreme focus on execution

QUALIFICATIONS

• Five (5) plus years of experience working with large disparate data sets, using machine learning to derive healthcare insights
• Experience with deep learning / GenAI
  • NLP, LLMs, Transformers, LSTM, GNNs, etc.
  • Experience with productionization is a plus.
• Experience with the following concepts: tree-based models (Random Forest, GBM, XGBoost, etc.), clustering models (K-means, KNN, KAMILA, DBSCAN, etc.), forecasting (ARIMA, Prophet, etc.), regression, anomaly detection, etc.
• Experience working with temporal, cross-sectional, and unstructured data
• Experience with git, including conducting & participating in code reviews
• Experience with Python and SQL
• Experience working with healthcare data
  • EMR, Claims, Midcycle Revenue, Clinical or Coding data experience a plus
• Strong written and oral communication skills
• Advanced degree (MS or higher) in applied data science, statistics, economics, computer science, computational natural sciences, or a related field

PREFERENCES

The following are preferred for this role but are not requirements:

• R and Java experience.
• H2O experience.
• AWS, Snowflake & Docker experience.
• Experience with ML Ops.
• Creating and maintaining private and/or open-source Python packages.

COMPENSATION

Compensation will be based on skills, experience, and performance.

ABOUT SIFT HEALTHCARE

Sift is a data science company working to improve payments operations and outcomes in the healthcare industry. We are a growing and dynamic team that is serious about technology. Based in Milwaukee, Wisconsin, Sift is thriving and looking for motivated team members who will help shape our culture. Sift offers competitive salaries and benefits. Learn more about Sift at www.sifthealthcare.com.

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