Accorded

Role Description We're looking for an experienced Actuary to join our lean actuarial team in a client-facing delivery role. You will support a portfolio of active accounts — running analyses, building and pressure-testing models, and communicating results directly to client stakeholders. Over time, you may take primary ownership of selected accounts. This is not a back-office actuarial position. You will be in the room (most often virtually) with clients regularly. The analytical and the relational are equally weighted here. - Execute client-facing actuarial analyses across our core methodologies: dynamic benchmarking, propensity score matching, and performance guarantee modeling - Build, validate, and explain financial models grounded in claims data — Medicare Advantage, commercial, and Medicaid - Own deliverables end-to-end: from data pull in BigQuery to a client-ready output that tells a coherent story - Participate in client calls and presentations; translate complex actuarial concepts for clinical and operational audiences without dumbing them down - Support scoping and methodology design for new engagements, including SOW input and assumptions documentation - Collaborate with data engineering and data science colleagues to improve model infrastructure and delivery pipelines - Identify gaps, surface risks, and propose solutions — proactively, not reactively Qualifications - ASA designation required; FSA a plus - 3+ years of actuarial experience in health (5+ preferred); consulting or payer background both welcome - Meaningful exposure to value-based care, population health analytics, or Medicare Advantage Requirements - Excel modeling: fluency with complex workbooks, not just pivot tables - SQL / BigQuery: able to write and debug queries independently against large claims datasets - AI tool proficiency: you actively use AI tools to accelerate your work, not as a novelty - Familiarity with common claims data sources (MarketScan, Komodo, CMS-RIF, or similar) is a plus Working Style - Clear communicator — written and verbal — with non-actuarial audiences - Comfortable owning a deliverable under time pressure without a playbook to follow - Organized enough to manage multiple concurrent client workstreams without dropping threads - Curious, not just compliant — you want to understand why the model says what it says What to Expect - Ambiguity is the default. Methodologies evolve, client needs shift, and the right answer is often something we're building for the first time. If you need a fully documented process before you can start, this role will frustrate you. - You will wear multiple hats. In the same week, you might QA a regression model, present findings to a CFO, and draft SOW language for a new engagement. Scope fluidity is a feature, not a bug. - The team is lean. There is no large actuarial department to absorb your questions or review your work six times before it goes to a client. Judgment and ownership matter from day one. - Remote means async-first. We are fully distributed. Strong written communication and self-direction are non-negotiable — not just nice to have. - The work is genuinely interesting. Our clients are building new care models. The actuarial questions they bring us have not all been answered before. That's the upside of the ambiguity. Benefits - Competitive base salary - Equity participation — we want teammates who are invested in what we're building - Fully remote, reasonably flexible working hours - Health, dental, and vision coverage offered - Support for continuing actuarial education and exam fees

Role Description Accorded is seeking an experienced data engineer to join our team. The ideal candidate will have a strong background in data engineering, proficiency in SQL, Python, and modern data engineering tools, and an eagerness to learn our business domain. - Build and maintain data transformation pipelines with robust testing to ensure data integrity. - Design, implement, and maintain models with complex domain and business logic for Accorded’s Acumen product. - Collaborate with cross-functional teams (such as our Actuarial Team) to understand data requirements and deliver high-quality solutions. - Participate in code reviews and maintain high standards of code quality. Qualifications - 5+ years of engineering experience with data products. - Strong proficiency in SQL and Python. - Extensive experience in managing data transformation pipelines. - Solid understanding of data modeling, data warehousing, and ETL processes. - Experience with version control systems (e.g., Git). - Strong problem-solving skills and attention to detail. - Excellent communication skills and ability to work in a collaborative environment. Requirements - Experience with dbt (data build tool) is highly preferred. - Experience with tools like BigQuery and Snowflake. - Knowledge of healthcare data and related regulatory requirements (e.g., HIPAA). - Experience with dbt-flux or similar incremental materialization frameworks. Additional Information - While healthcare experience is not strictly required, a willingness and enthusiasm to learn about the healthcare domain is essential. - You will work closely with subject matter experts to understand domain-specific requirements and challenges. - Accorded is located in the San Francisco Bay Area. Remote candidates living and authorized to work in the continental United States are eligible to apply. - Accorded is an Equal Opportunity Employer. We are committed to creating a diverse and inclusive work environment and do not discriminate on the basis of race, color, religion, gender, gender identity, sexual orientation, national origin, genetics, disability, age, or veteran status.