• Own the end-to-end lifecycle of production machine learning models, from problem definition through deployment and ongoing optimisation. • Design, build and deploy artificial neural network and machine learning models for vehicle valuation, pricing and other analytics. • Take responsibility for production model performance, reliability and long-term maintenance. • Evaluate model performance and improve predictive accuracy across production models. • Develop and maintain automated retraining pipelines to keep models effective over time. • Monitor deployed models, investigate issues and implement improvements to ensure models remain accurate and reliable. • Design and run experiments, track results and use data to drive model improvements. • Work closely with engineering and product teams to integrate models into production systems and deliver business value.

• Provide data management support by assisting with data processing, including downloading, processing, cleaning, documenting, consolidating, archiving, and transferring of data in various files formats. • Provide data management support to by posting of data in various file formats and locations. • Document the development and implementation of data collection methods and protocols. • Manage and update Power BI dashboard. • Experience modernizing surveillance systems, including but not limited to converting SAS code to Python/R. • Automate reoccurring reports, tables, and presentations of data for the team to access on a routine basis. • Create and manage quality assurance programs for daily downloads from website. • Provide analytic support including regular and ad hoc epidemiologic and statistical analyses. • Produce reports, tables, and presentations of the data.

Role Description Immediate Full-Time Position for Senior Data Scientist (This will be FTE only). - Design, develop, and deploy end-to-end AI/ML solutions for predictive modeling, risk stratification, behavioral analytics, and treatment pathway prediction. - Build advanced NLP, LLM, and RAG-based applications, including prompt engineering, fine-tuning, and clinical AI guardrails for extracting insights from unstructured data. - Develop speech AI and conversational AI capabilities using ASR, sentiment analysis, intent classification, Text-to-SQL, and decision-support models to improve care outcomes. - Measure model performance through A/B testing, cohort analysis, explainability (SHAP/LIME), drift monitoring, and HIPAA-compliant governance. - Collaborate with Data Engineering to implement feature stores, MLflow, MLOps, CI/CD pipelines, and scalable real-time/batch inference solutions. - Mentor junior data scientists, evaluate emerging AI technologies, and drive the AI roadmap by translating advanced models into actionable healthcare solutions. Qualifications - 7+ years of hands-on data science experience building and deploying predictive analytics, NLP, and Generative AI solutions in production, preferably within healthcare or other regulated industries. - Proven expertise across the entire machine learning lifecycle, including feature engineering, model development, deployment, monitoring, and optimization. - Advanced Python skills with pandas, NumPy, scikit-learn, PyTorch, and TensorFlow, along with classical ML techniques such as XGBoost, LightGBM, survival analysis, time-series forecasting, and deep learning. - Strong experience with LLMs, RAG architectures, transformer models (BERT/GPT), Hugging Face, LangChain, vector databases, and LLM fine-tuning and evaluation. - Hands-on expertise with NLP, speech AI, Databricks (Delta Lake, MLflow, Spark), AWS (S3, SageMaker, Bedrock, Redshift, Athena), SQL, Docker, Kubernetes, and MLOps practices. - Demonstrated leadership through mentoring, cross-functional collaboration, and the ability to communicate complex AI/ML insights to technical and business stakeholders while driving innovation and best practices. Company Description

• Lead and mentor a team responsible for data operations, including data integration, monitoring, and issue resolution. • Oversee the health, performance, and reliability of multiple inbound and outbound data feeds, including clinical, attribution, and demographic data. • Monitor and troubleshoot data processing issues, ensuring timely identification and resolution of integration errors within the data interface engine. • Manage and optimize Carina’s data technology tools (such as Rhapsody, NextGate, and DevOps) including overseeing configuration and performance tuning, maintaining communication with support teams, and providing ongoing support of data exchange processes. • Manage relationships with technology vendors and external partners, including service performance, issue escalation, contract coordination, and strategic roadmap planning. • Oversee the enterprise master patient index (EMPI), ensuring accurate patient matching across millions of unique records through governance, monitoring, and tuning of matching algorithms. • Establish and maintain processes for data validation, reconciliation, and quality assurance across systems. • Ensure secure and compliant data handling practices aligned with HIPAA and other regulatory requirements. • Facilitate strategic collaboration with internal and external stakeholders to manage data integration requirements and ensure system interoperability. • Drive improvements in data operations efficiency, automation, and reliability. • Maintain clear documentation of data flows, integration processes, and operational procedures. • Oversee incident management, root cause analysis, and continuous improvement initiatives. • Supervise and coordinate daily activities of the Data Operations team. • Provide leadership, mentorship, and performance management to staff. • Ensure operational coverage and timely resolution of data-related issues. • Monitor team performance and ensure adherence to service level expectations. • Promote a culture of accountability, collaboration, and continuous improvement.