Role Description We are seeking a Data Scientist to join our growing Strategic Analytics, Value, and Economics team. In this role, you’ll leverage advanced data science and health economics methods to help shape access to life-saving therapies and innovations. You’ll work with rich, real-world healthcare data including Medicare and Medicaid claims to uncover insights that directly inform policy, pricing, and patient access decisions across the life sciences sector. This position offers the opportunity to apply your analytical expertise to real-world evidence (RWE), health outcomes, and market access challenges while making a measurable impact on how treatments reach the patients who need them most. The person in this role will perform healthcare claims-based analytics for a variety of internal and client-facing teams. Analytics work will include health economics and outcomes research (HEOR), market basket assessment of diseases or treatment usage, and related evidence-generation studies. Job Duties - Designing and executing analyses in Medicare and Medicaid healthcare claims - Lead in the development and production of deliverables (Excel workbooks and PowerPoint decks) as well as communicating results to shareholders - Manage data analysts and assist in the QA of programs and analyses Qualifications - Master’s or PhD in Data Science, Biostatistics, Health Economics, Epidemiology, Public Health, Computer Science, or a related quantitative field - At least 3 years of professional experience with SAS, SQL, or other relevant programming experience applying data science in healthcare, HEOR, or life sciences - Demonstrated experience with large-scale health data analysis (claims, EHR, registry, or clinical trial data) - Experience working with data offered in the CMS’ Chronic Condition Warehouse - Experience working in the Virtual Research Data Center (VRDC) offered by CCW - Experience working with data in Medicare Standard Analytic Files (SAF), Research Identifiable Files (RIF), or Medicaid T-MSIS data Location Candidates can be based anywhere in the U.S., with a preference for those operating in the Eastern or Central Standard Time Zone. Candidates based in Washington, DC or Austin, TX, will have the option of hybrid work arrangements. Compensation and Benefits The salary range is $90,000-$140,000 annual base salary plus bonus plan. Exceptionally qualified candidates will be evaluated according to experience levels. Please include your salary requirements with your application if they exceed the posted range. ADVI offers an outstanding benefits package, including the following: - Medical, dental, and vision - 8 paid holidays, including one ADVI Anniversary Day per calendar year - 401(k) retirement contribution match, up to 3 percent of salary, with immediate vesting - Health Reimbursement Account - Life and short-term and long-term disability insurance - Paid vacation and sick leave Diversity Statement ADVI’s commitment to diversity, equity, inclusion, and collaboration is key to building extraordinary teams. We hire people with exceptional talents, abilities, and potential, then build an environment where you can become the best version of yourself. Our Vision To be the leading and most knowledgeable go-to-market access and commercialization partner for life sciences and healthcare innovators worldwide. Our Mission To provide life science and healthcare innovators the benefit of our team’s wisdom, empathy, and creativity that, through data-informed strategy, generates evidence to optimize outcomes and, through tech-enabled access solutions, creates opportunities and expands care. Our Values - Act with Integrity - Strive for Excellence - Make an Impact - Think smart, Stay curious - Celebrate the Journey, not just the results We look forward to hearing from you! #LI-Remote

• Desenvolver, validar e evoluir modelos estatísticos e de Machine Learning, garantindo performance, estabilidade e explicabilidade • Conduzir análises de ponta a ponta: exploração, preparação, modelagem e entrega • Aplicar técnicas de modelagem preditiva, clustering, detecção de anomalias e forecasting em problemas de negócio • Trabalhar com grandes volumes de dados, garantindo qualidade, integridade e coerência estatística • Atuar em casos de uso estratégicos, traduzindo necessidades de negócio em soluções analíticas orientadas a dados • Apoiar a colocação de modelos em produção em colaboração com times de engenharia de dados e MLOps • Comunicar resultados e insights de forma clara para públicos técnicos e de negócio • Atuar de forma colaborativa com times multidisciplinares (engenharia, analytics, produto e negócio)

Role Description As a Principal Data Scientist at Kainos, you will be accountable for the successful delivery of large-scale, high-impact AI solutions that leverage state-of-the-art machine learning, generative, and agentic AI technologies. You will help set the direction for AI and data science across the business, driving the adoption of modern AI development practices and scalable, cloud-native architectures at enterprise scale. - Provide technical and thought leadership, engaging with C-level and senior stakeholders to define architectural principles and strategic direction. - Foster a culture of innovation, continuous learning, and engineering excellence—both within Kainos and across the wider industry. - Lead, mentor, and develop a community of data scientists, AI engineers, and technical managers, ensuring the adoption of robust standards and responsible AI practices. - Build enduring customer relationships and proactively develop new alliances with technology partners. - Shape Kainos’ commercial AI offerings and embed commercial acumen to influence account strategies. - Ensure customers get measurable business value from AI investments. Qualifications - Proven track record of accountability for the delivery of complex, production-grade AI/ML solutions at scale. - Demonstrable experience of technical leadership in AI delivery. - Deep expertise in developing and assuring advanced AI/ML models, including time series, supervised/unsupervised learning, reinforcement learning, LLMs, and agentic AI. - Experience with the latest AI engineering approaches such as prompt engineering, retrieval-augmented generation (RAG), and orchestration of agentic AI systems. - Expertise in data engineering for AI: handling large-scale, unstructured, and multimodal data, and integrating non-traditional data sources. - Deep understanding of responsible AI principles, model interpretability, and ethical considerations, with a track record of influencing policy and standards. - Ability to communicate and negotiate with C-level and senior stakeholders, translating complex technical concepts into business value. - Experience in developing and executing account strategies, shaping commercial AI offerings, and driving business development in partnership with sales and account managers. - Demonstrated ability to build and lead high-performing teams and wider AI and data science communities. - Strong commercial acumen with a history of influencing the commercial success of AI products and solutions. Requirements - Experience with modern deep learning frameworks (e.g., PyTorch, TensorFlow), fine-tuning or distillation of LLMs (e.g., GPT, Llama, Claude, Gemini), and advanced ML libraries (e.g., scikit-learn, XGBoost). - Experience with data storage for AI, vector databases, semantic search, and knowledge graphs. - Active contribution to open-source AI projects, research publications, and industry events/websites. - Familiarity with AI security, privacy, and compliance standards (e.g., ISO 42001). Benefits - Supportive and inclusive work environment. - Opportunities for continuous learning and professional growth. - Engagement in diverse and innovative projects. Company Description Kainos is recognised as one of the UK’s leading AI and data businesses, with a decade-long track record of delivering impactful, production-grade AI solutions for clients across government, healthcare, defence, and commercial sectors. Kainos is at the forefront of AI innovation, trusted by Microsoft, AWS, and others to deliver advanced AI and data solutions at citizen scale. - 150-strong AI and Data Practice with deep expertise in machine learning, generative AI, agentic AI, and data. - Pioneers in responsible AI, having authored the UK government’s AI Cyber Security Code of Practice implementation guide. - Commitment to ethical, secure, and measurable AI deployment.

Role Description Neo.Tax is seeking a Senior Data Scientist + Machine Learning Engineer (combo role) to build and ship models and production ML systems that power our core product experiences and automate complex tax and accounting workflows. This role is hands-on and product-oriented: you will take ambiguous problems, turn them into measurable objectives, build robust solutions, and collaborate closely with engineering and product to deploy and iterate in production. We are a remote company, but we prefer to hire in time zones that can overlap with our HQ in San Francisco, CA! Responsibilities - Own ML/AI problem spaces end-to-end: - Define success metrics, create baselines, iterate on approaches, and drive projects from prototype to production. - Model development: - Build and improve models spanning classification, information extraction, entity resolution, clustering, ranking, anomaly detection, and forecasting. - LLM systems: - Design and evaluate prompt + retrieval + tool-calling pipelines; improve quality through datasets, labeling, and systematic evaluation. - Data foundations: - Define datasets, labeling strategies, and data quality checks; build features that generalize across customer contexts. - Experimentation and evaluation: - Design offline evaluations and online experiments; build dashboards and monitoring to detect regressions. - Production ML engineering: - Build and operate training/inference pipelines (batch and/or online), model serving, feature/data pipelines, and monitoring/alerting for quality, latency, and cost. - Partner with engineering: - Collaborate on productionization, scalability, reliability, latency, and cost; contribute directly to model-serving or batch pipelines as needed. - Cross-functional collaboration: - Work with product, engineering, and customer-facing teams to understand workflows and translate real customer pain into ML deliverables. - Technical communication: - Write clear specs and postmortems, document trade-offs, and communicate progress, risks, and decisions. Qualifications - MS/PhD in Computer Science, Statistics, Mathematics, or a related quantitative field, or equivalent practical experience. - 6+ years of industry experience as a Data Scientist / Applied Scientist / ML Engineer shipping ML to production (or equivalent). - Strong proficiency in Python and the modern data/ML ecosystem (NumPy/Pandas, scikit-learn, PyTorch or TensorFlow). - Strong understanding of statistical modeling, experimentation, and evaluation (metrics, confidence intervals, A/B testing, bias/variance, error analysis). - Experience building data pipelines and working with SQL and relational databases. - Experience deploying and maintaining models in production (batch or real-time), including monitoring and iteration; comfortable owning operational concerns (reliability, latency, cost). - Ability to operate with high ownership in ambiguous environments; strong communication and collaboration skills. - Ability to effectively design and implement solutions without the help of AI. - Experience with LLM evaluation, synthetic data generation, RAG, or tool-augmented agents. Bonus - Experience with information extraction and document understanding. - Experience with distributed data processing (e.g., Spark, Beam) and/or workflow engines. - Experience with GCP, AWS, or Azure. - Experience working at early-stage, venture-backed startups. Benefits - Salary range: $190,000-210,000 - Stock Option Plan (Equity) - Health Care Plans (Medical, Dental, Vision, Short-term Disability) - 90% coverage for individual + family - Health & Wellness subsidy - Retirement Plan (401k) - Paid Time Off (Vacation, Sick & Public Holidays) - Family Leave (Maternity, Paternity) - Work From Home option