Sift Healthcare

👥 11-50💰 $20,000,000 Series B 11 months agoArtificial Intelligence (AI)Information ServicesPredictive AnalyticsInsurTechHealth CareFinTechSoftware💼 Private Company
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Sift Healthcare is a data science company revolutionizing healthcare payments. We build and deploy a Payments Intelligence Platform that uses machine learning and predictive analytics to reduce insurance denials, maximize patient payments, and optimize revenue cycle operations for healthcare organizations. Our platform provides actionable insights, accelerating insurance payments, minimizing denials, and improving patient collections. We're making a significant impact by enabling data-driven decision-making in a traditionally complex and inefficient sector. Our engineering team leverages a robust tech stack including Ruby on Rails, Python, SQL, and cloud technologies such as AWS and Snowflake. We prioritize building scalable and maintainable solutions, fostering a collaborative and innovative environment. We encourage our data scientists to explore and implement cutting-edge machine learning techniques, contributing directly to product development and client success. We value creativity, teamwork, and a commitment to excellence in everything we do. Located in Milwaukee, Wisconsin, Sift Healthcare is a rapidly growing company with a strong track record of success. We've secured over $36 million in funding and serve a diverse range of clients, including large health systems, leading HCIT vendors, payers, and revenue management agencies. We offer competitive salaries and benefits, and while we are based in Milwaukee, we also consider remote candidates for suitable roles. We are passionate about improving healthcare payments and empowering healthcare organizations with the data-driven insights they need to thrive. Join our team and help us build the future of healthcare payments!

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🔍 Healthcare

  • Healthcare industry knowledge and data experience preferred
  • Three (3) plus years of experience creating dashboards and ad hoc reports
  • Experience in sourcing, organizing, and updating reporting data from the appropriate in-house database
  • Ability to manipulate data and investigate issues
  • Basic statistical knowledge and experience with advanced Excel formulas
  • SQL experience is required
  • Experience with a large-scale BI tool is required; experience with Sisense BI tool is a plus
  • Experience building creative visualizations and dashboards utilizing existing widgets provided within the packaged software
  • Ability to quickly switch priorities and work in a multi-project, fast-paced startup environment
  • Diligent and motivated to work independently
  • Strong communication with both technical and non-technical stakeholders
  • Enhance BI dashboards based on business-created specifications to drive efficiency in reporting and analysis – focused on UX and scalability
  • Continuous Improvement of Sift’s current library of reports and dashboards
  • Assist in dashboard data cube and data model QA
  • Work with data engineers and product analysts to ensure format changes and client specifications are implemented correctly, accurately, and uniformly
  • Assist in ad hoc analysis and report design for internal analysts and stakeholders
  • Assist in documenting, testing, and utilizing Generative BI frameworks
Posted 27 days ago
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🔥 Principal ML Ops Engineer
Posted about 1 month ago

📍 United States, Canada

🧭 Full-Time

🔍 Healthcare Data Science

  • Master's degree in Computer Science or related field
  • 5+ years as ML Ops Engineer or Data Scientist
  • Expertise with infrastructure-as-code frameworks
  • Strong understanding of CI/CD pipelines and containerization
  • Experience with cloud platforms
  • Familiarity with monitoring tools
  • Experience with healthcare data
  • Design and implement ML Ops infrastructure
  • Develop CI/CD pipelines for model serving
  • Maintain monitoring systems for model performance
  • Utilize containerization and orchestration tools
  • Collaborate with data teams for production readiness
  • Champion ML Ops best practices
  • Integrate new technologies into the platform
  • Provide technical guidance to the team

AWSDockerKubernetesMachine LearningCI/CDTerraform

Posted about 1 month ago
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🔥 AI Scientist
Posted about 1 month ago

📍 Remote

🔍 Healthcare

  • Advanced degree (Ph.D. or Master's) in Computer Science, AI, or related field with a research focus.
  • 3+ years of AI/ML research experience, specializing in NLP and Generative AI.
  • Deep understanding of LLMs, agent architectures, and reinforcement learning.
  • Proficient in Python and foundational frameworks and libraries (e.g., PyTorch, TensorFlow).
  • Experience with LLM-related NLP techniques (transformers, attention mechanisms), data analysis, statistical modeling, and ML evaluation metrics.
  • Experience with vector search and search optimization techniques for RAG/CRAG.
  • Experience with LangChain/LangGraph (or similar) and LLM training/deployment on cloud infrastructure (AWS, GCP, Azure preferred).
  • Strong analytical, problem-solving, communication, and collaboration skills; ability to work independently and in teams. Healthcare data/revenue cycle experience a strong plus.
  • Conduct cutting-edge research on LLMs and Generative AI agents to automate key revenue cycle processes, including exploring novel agent architectures (hierarchical, multi-agent, reinforcement learning-based).
  • Develop and implement advanced prompt engineering techniques to optimize LLM behavior within complex agent workflows.
  • Design, implement, and analyze experiments to evaluate and optimize LLM and agent performance on customer-focused and infrastructure tasks, focusing on robustness, explainability, adaptability, and bias mitigation for responsible use.
  • Utilize frameworks like LangChain or LangGraph to build and experiment with complex agent workflows.
  • Collaborate with engineering, ML Ops, and product teams to research and develop Generative AI training infrastructure and data pipelines.
  • Stay current with LLM and agent research, sharing findings, contributing to AI strategy, and guiding offshore teams on technical requirements and POCs.
  • Document research methods, findings, and recommendations, and transition research prototypes into deployable solutions.

AWSPythonArtificial IntelligenceData AnalysisGCPMachine LearningPyTorchAlgorithmsAzureData engineeringREST APITensorflowJSON

Posted about 1 month ago
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🔥 Data Scientist III
Posted 5 months ago

📍 United States

🔍 Healthcare

  • Four (4) plus years of experience working with large disparate data sets, using quantitative and qualitative analysis to derive business insights and leverage ML.
  • Healthcare data experience is required. EMR (Epic, Cerner) or EDI (claim and remittance) is strongly preferred.
  • Python and SQL experience required. R experience is a plus.
  • Experience with feature engineering and creation is required.
  • Experience with supervised ML is required, including tree-based ML (Random Forest, GBM, XGBoost, etc.).
  • Experience with unsupervised ML and encoding is strongly preferred (clustering, Transformers, LSTM, etc.).
  • Strong communication skills, both oral and written.
  • Must be a team player and willing to collaborate and assist members of the team.
  • An advanced degree (MS or higher) in applied data science, statistics, economics, computer science, or a related field is preferred.
  • AWS Cloud experience is a plus.
  • Snowflake experience is a plus.
  • Act as a key contributor to the development of Sift’s current RevCollect Denials Prioritization ML products and pipelines.
  • Operationalize ML for client launches.
  • Develop ML pipelines for new product features.
  • Enhance ML through attribute ideation and creation.
  • Investigate and manipulate large datasets to uncover and resolve issues.
  • Contribute to Sift’s ML Ops initiatives.
  • Work and communicate effectively across teams.

PythonSQLMachine LearningData scienceCommunication Skills

Posted 5 months ago
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