This is a job that Jill, our AI Recruiter, is recruiting for on behalf of one of our customers. She will pick the best candidates from Jack's network. The next step is to speak to Jack. Founding Applied Data Scientist ($100k-$200k + Equity) at Bluevia Health Company Description: Bluevia Health - Mayo Clinic partnered AI startup Job Description: As the founding data scientist at this early-stage healthcare AI company, you will own the end-to-end loop from raw clinical data to deployable models. Working with petabyte-scale EHR data from the Mayo Clinic, you’ll build the foundations for predicting post-surgical complications, directly impacting patient outcomes across a 21-site US health system. Why this role is remarkable: - Rare access to 10M+ longitudinal patient records and 5.5 petabytes of rich clinical data through a live Mayo Clinic partnership. - Massive real-world impact with an accelerated deployment timeline into a major 21-site US health system already underway. - High-ownership founding role in a lean team of four, where your technical decisions define the company’s core AI platform. What you will do: - Build standardization pipelines and foundations to transform raw, messy EHR tables into analysis-ready longitudinal datasets. - Design and validate rule-based computed phenotypes for clinical complications across diverse specialties and patient subgroups. - Develop and benchmark predictive models, starting with XGBoost and iterating toward LLM-extracted features and multimodal representations. The ideal candidate: - Strong Python and SQL skills with proven experience building data pipelines and feature sets from complex, raw sources. - Expertise in longitudinal event data and temporal reasoning, preferably within a healthcare, EHR, or claims data context. - High-agency problem solver who can move from ambiguous clinical questions to rigorous, validated, and deployable model outputs. Who are Jack & Jill? Ok, I'll go first. I'm Jack, an AI Career Agent that gets to know you on a quick call, learning what you're great at and what you want from your career. Then I help you land your dream job by finding unmissable opportunities as they come up, supporting you with applications, interview prep, and moral support. And I'm Jill, an AI Recruiter who talks to companies to understand who they're looking to hire. Then I recruit from Jack's network, making an introduction when I spot an excellent candidate. Next steps Step 1. Visit our website. Step 2. Click 'Talk to Jack'. Step 3. Talk to Jack so he can understand your experience and ambitions. Step 4. Jack will make sure Jill (the AI agent working for the company) considers you for this role. Step 5. If Jill thinks you're a great fit and her client wants to meet you, they will make the introduction. Step 6. If not, Jack will find you excellent alternatives. All for free. We never post fake jobs This isn't a trick. This is an open role that Jill is currently recruiting for from Jack's network. Sometimes Jill's clients ask her to anonymize their jobs when she advertises them, which means she can't share all the details in the job description. We appreciate this can make them look a bit suspect, but there isn't much we can do about it. Give Jack a spin! You could land this role. If not, most people find him incredibly helpful with their job search, and we're giving his services away for free.

Please submit your CV in English and indicate your level of English proficiency. Mindrift connects specialists with project-based AI opportunities for leading tech companies, focused on testing, evaluating, and improving AI systems. Participation is project-based, not permanent employment. What this opportunity involves While each project involves unique tasks, contributors may: - Design rigorous statistics problems reflecting professional practice; - Evaluate AI solutions for correctness, assumptions, and constraints; - Validate calculations or simulations using Python (NumPy, Pandas, SciPy, Statsmodels, and Scikit-learn); - Improve AI reasoning to align with industry-standard logic; - Apply structured scoring criteria to multi-step problems. What we look for This opportunity is a good fit for statisticians with an experience in python open to part-time, non-permanent projects. Ideally, contributors will have:  - Degree in Statistics or related fields, e.g. Probability Theory, Mathematical Statistics, Applied Statistics, etc. - 3+ years of professional mathematics experience - Strong written English (C1/C2) - Strong Python proficiency for numerical validation - Stable internet connection  Professional certifications (e.g., PStat, CAP, SAS Certifications) and experience in international or applied projects are an advantage. How it works Apply → Pass qualification(s) → Join a project → Complete tasks → Get paid Project time expectations For this project, tasks are estimated to require around 10–20 hours per week during active phases, based on project requirements. This is an estimate, not a guaranteed workload, and applies only while the project is active. Compensation On this project, contributors can earn up to $73 per hour equivalent, depending on their level and pace of contribution. Compensation varies across projects depending on scope, complexity, and required expertise. Please note that other projects on the platform may offer different earning levels based on their requirements.

Please submit your CV in English and indicate your level of English proficiency. Mindrift connects specialists with project-based AI opportunities for leading tech companies, focused on testing, evaluating, and improving AI systems. Participation is project-based, not permanent employment. What this opportunity involves While each project involves unique tasks, contributors may: - Design rigorous statistics problems reflecting professional practice; - Evaluate AI solutions for correctness, assumptions, and constraints; - Validate calculations or simulations using Python (NumPy, Pandas, SciPy, Statsmodels, and Scikit-learn); - Improve AI reasoning to align with industry-standard logic; - Apply structured scoring criteria to multi-step problems. What we look for This opportunity is a good fit for statisticians with an experience in python open to part-time, non-permanent projects. Ideally, contributors will have:  - Degree in Statistics or related fields, e.g. Probability Theory, Mathematical Statistics, Applied Statistics, etc. - 3+ years of professional mathematics experience - Strong written English (C1/C2) - Strong Python proficiency for numerical validation - Stable internet connection  Professional certifications (e.g., PStat, CAP, SAS Certifications) and experience in international or applied projects are an advantage. How it works Apply → Pass qualification(s) → Join a project → Complete tasks → Get paid Project time expectations For this project, tasks are estimated to require around 10–20 hours per week during active phases, based on project requirements. This is an estimate, not a guaranteed workload, and applies only while the project is active. Compensation On this project, contributors can earn up to $73 per hour equivalent, depending on their level and pace of contribution. Compensation varies across projects depending on scope, complexity, and required expertise. Please note that other projects on the platform may offer different earning levels based on their requirements.

Benefits: - 401(k) matching - Competitive salary - Health insurance - Paid time off About this Role: In this role, you will provide computational, data science, and bioinformatics support for Office of Research Innovation, Validation, and Application’s (ORIVA) research validation and application programs across D-NICEATM and DAIBR. You will develop and maintain NIH databases, build analytical tools, support computational modeling, and deliver data-driven insights to a multidisciplinary team advancing human-centered biomedical research. This role sits at the intersection of data science, regulatory science, and biomedical research. Key Responsibilities: - Develop and execute analytical workflows to process, analyze, and interpret large-scale biomedical datasets - Apply computational and bioinformatics methods in support of New Approach Methodologies (NAMs) related research objectives - Maintain and enhance NIH databases and tools through data curation, integration, and interoperability support - Build and maintain data pipelines and analytical tools using Python, R, or equivalent languages - Develop and update user support materials, websites, and training resources - Ensure all published materials meet 508-compliance standards - Present complex analytical results clearly to scientific and non-technical audiences - Support data validation, cleansing, and governance per NIH data quality standards Qualifications and Skills: - PhD in bioinformatics, mathematics, statistics, computer science, data science, or related field with 4+ years of relevant experience OR Master's degree in an equivalent field with 4 years of additional experience - Proficiency in at least two programming languages: Python, R, Perl, or equivalent - Experience with bioinformatics tools, databases, and high-throughput data analysis - Experience managing and integrating large biomedical or genomic datasets - Strong background in statistical analysis, data modeling, and computational methods - U.S. citizenship required; ability to obtain Public Trust clearance Desired Skills and Competencies: - Expertise in NAMs or computational toxicology - Experience with NIH scientific databases and platforms - Familiarity with in silico modeling, Adverse Outcome Pathway (AOP) frameworks, or ICCVAM/OECD validation standards - Prior NIH and/or HHS contractor experience - Experience with cloud platforms or HPC environments - Peer-reviewed publications in a related field Equal Opportunity Employer: We are an Equal Opportunity Employer and do not discriminate in employment decisions on the basis of race, color, religion, sex (including pregnancy, sexual orientation, or gender identity), national origin, age, disability, genetic information, veteran status, or any other status protected by applicable federal, state, or local laws. All employment decisions are based on business needs, job requirements, and individual qualifications. Flexible work from home options available.