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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Healthcare Decision Scientist - **Company:** Cambia Health Solutions, Inc. - **Location:** Minot, ND, United States (Remote available) - **Experience:** Expert - **Salary:** $105,000.0 - $172,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Data Analysis, Artificial Neural Networks, Unit Testing, Bioinformatics, Cluster Analysis, Databases, Continuous Integration, Data Mining, Programming Tools, Monitoring of Systems, Python (Programming Language), Machine Learning, Natural Language Processing, Power BI, Software Engineering, Tableau (Software), Unstructured Data, Data Processing, Scripting, Freeform SQL, Real Time Systems, Deep Learning, Agentic-AI, Information Technology, Xgboost, Machine Learning Operations, Software Version Control, Recurrent Neural Networks - **Published:** October 3, 2026 - **Apply:** https://www.disabledperson.com/jobs/75726540-healthcare-decision-scientist ## About the Role Do you have the curiosity of a scientist, the pragmatism of a consultant, and the communication skills of a trusted advisor? Do you thrive on turning data into decisions that drive measurable business outcomes? Then this role may be the perfect fit., Decision Scientist II: Master's degree (PhD preferred) in a strongly quantitative field such as Statistics, Applied Mathematics, Physics, Operations Research, Computer Science, Bioinformatics, or Econometrics and 3+ years of progressive, related work experience. In lieu of an advanced degree, a BA/BS degree with 5 years of related work experience will be considered. Decision Scientist III: Master's degree (PhD preferred) in a strongly quantitative field such as Statistics, Applied Mathematics, Physics, Operations Research, Computer Science, Bioinformatics, or Econometrics and 5+ years of progressive, related work experience. In lieu of an advanced degree, a BA/BS degree with 8 years of related work experience will be considered. Skills and Attributes: *Ability to think creatively and demonstrate strong analytical skills, analyzing complex situations both independently and as part of a team, learning quickly and synthesizing solutions, options and action plans. *Familiarity with mixed methods research, with experience in at least two of the following: advanced analytics (statistics, simulation, optimization, time series, longitudinal studies, life event modeling); data mining, NLP, machine learning (regression, clustering, neural networks, kernel methods, dimensionality reduction, ensemble methods, decision trees) and deep learning (CNN, LSTM, GAN); building solutions with tools for data mining, statistics, analysis and scripting (e.g., Python). *Experience cleaning, aggregating, and pre-processing data from varied sources, and creating complex SQL queries for both standard and ad-hoc data mining purposes. *Demonstrated ability to apply quantitative analysis techniques to business situations, including forecasting, descriptive statistics, statistical inference, and multivariate modeling. *Ability to analyze and interpret qualitative data (research, feedback) and incorporate those insights into quantitative analyses. * Proficiency with a range of business intelligence and analysis tools (R, Power BI, or Tableau) and at least one statistical/analytical programming tool (Python, R, etc.). *Project experience with machine learning, data mining, and constructing analytical models and algorithms. *Experience with fundamental software engineering practices (e.g., version control, unit testing, CI/CD). *Ability to access and process structured and unstructured data in various databases and formats. *Ability to coordinate cross-functionally and manage time and tasks effectively to drive solutions and resolve issues in a timely manner. *Excellent oral and written communication skills to effectively interface with a broad array of internal and external contacts, including leadership. *Additional for Decision Scientist II: Proven ability to provide analysis and data interpretation in support of strategy development, program implementation and evaluation; deep understanding of various machine learning algorithms and when to apply them; ability to maintain end-to-end ML models; ability to work with minimal direction; ability to distill informal requirements into problem definitions amid ambiguity; recognized as a technical leader by peers. *Additional for Decision Scientist III: Ability to design systems across batch, streaming, and real-time processing; ability to evaluate cutting-edge ML research and frameworks; familiarity with semi-supervised, reinforcement, transfer, and graph-based learning; ability to simplify and improve the full ML model life cycle; strong facilitation and consensus-building skills; proven ability to influence others; ability to build ML pipelines through full ML cycles; ability to effectively lead teams without direct supervisory responsibility. *Experience with AI tools and technologies to enhance productivity and decision-making in professional settings highly desired. ## Description *Design and execute analyses that uncover opportunities for business improvement and connect data, performance, and business strategy. *Collaborate with stakeholders across sales, operational, clinical, finance, and provider functions to frame ambiguous challenges into structured analytical questions, identifying decision options, tradeoffs, risks, and expected outcomes. *Select and apply appropriate analytical techniques (e.g., XGBoost, regression, clustering, forecasting, anomaly detection, causal analysis, experimental design) to develop predictive, descriptive, classification, segmentation, and optimization models that balance sophistication with practical applicability. *Partner with business teams to embed insights into operational workflows, measuring intervention impact and refining approaches to deliver measurable business value. *Present findings and facilitate decision-making conversations with leaders at all levels, translating complex analytical concepts into clear, actionable recommendations for non-technical audiences. *Develop scalable analytical frameworks and decision-support capabilities, and contribute to MLOps, model monitoring, and agentic AI evaluation to ensure ongoing accuracy and reliability of deployed solutions. * Incubate and evolve agentic intelligence capabilities that augment analytical insights and operationalize predictive modeling outputs. (For Decision Scientist III: take initiative to pursue larger-scope projects, recommend improvements to methods and complex algorithms, educate stakeholders to drive organizational buy-in, and mentor junior Decision Scientists.) ## Related Videos - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [JavaScript? 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