Accelerant

Data Engineer

• Define and evolve the Accelerant Data Platform by gathering stakeholder requirements.
• Identify opportunities to deliver value through data-driven solutions enabling Risk Exchange efficiency.
• Collaborate with Product Managers, Engineers, and Designers to deliver high-quality solutions.
• Develop and own roadmap for data ingestion and consumption with Outcome and Key Results (OKRs).
• Communicate strategy and platform outcomes to various levels within the company.

Product Manager – Data Platform

Data Scientist

• Develop machine learning and AI systems that improve decisions across pricing, underwriting, portfolio management, operations, and claims.
• Work across structured data, text, documents, and external data sources, applying statistical modeling, modern machine learning, AI and agentic workflows to solve challenging real-world problems.
• Identify the right approach, build production-ready solutions, and measure the business impact of your work.
• Tackle a broad range of machine learning and AI problems such as predictive modeling, classification, ranking, matching, recommendation, anomaly detection, information extraction, entity resolution, building high-quality datasets, and automating analytical and decision-making workflows.

Principal Data Scientist – Machine Learning, AI

DevOps Engineer

• Drive the reliability and observability initiative
• Own the reliability roadmap end to end.
• Prove a repeatable define → emit → ingest → dashboard → alert metric pipeline, set SLOs and error budgets, prioritize the work, and drive execution.
• You'll partner with engineering on what we monitor, how, and when — indexing on user impact over low-level infrastructure.
• Harden the foundational platform
• Take the financial data platform from functional to enterprise-grade, with a focus on availability, performance, and recoverability.
• Strengthen deployment paths, straight-through processing, and failover so the monthly close runs faster and cleaner as legacy hops are retired.
• Expand observability breadth and depth
• Extend instrumentation across the six target systems — Velocity, Red Panda, MuleSoft, Snowflake, Fabric, and AWS (with D365 ledger to follow) — proving both push (OpenTelemetry) and pull (agent) ingestion.
• Cover service health (latency, error rates, throughput) and business KPIs (match rate, reconciliation completeness, settlement correctness and latency).
• Implement a scalable incident and review process
• Build the on-call, alerting, and blameless postmortem process that keeps reliability high as systems and the team grow.
• Route alerts Datadog → Incident.io with ServiceNow as the system of record, and set severity standards, escalation norms, and follow-up tracking that actually closes the loop.
• Scale automation, auditability, and reduce toil
• Build the tooling that automates routine operations, self-heals common failures, and surfaces signal over noise.
• Establish data lineage and retention, and validate reliability at scale — 5,000+ transactions before go-live — through auto-remediation, capacity planning, and actionable dashboards.
• Build specialized SRE agents using Cursor AI
• Design and ship AI agents for incident triage, log analysis, and root-cause investigation (to name a few).
• Use Cursor as your build environment.
• Treat the agents as products solving specific problems.
• Host SRE agents on the AI fabric
• Partner with the AI platform team to deploy your agents on the org's AI fabric. Make them discoverable, governed, and reusable across functions.

Senior SRE

Paralegal

• Assist attorneys in preparing legal documents and correspondence
• Conduct legal research and analysis
• Manage and organize legal files and documents
• Assist attorneys in drafting various legal documents, including board resolutions
• Take meeting minutes and prepare board documentation
• Perform certain corporate secretarial duties
• Prepare presentations, reports, and summaries for a variety of audiences
• Prepare and submit regulatory and legal filings
• Review, track and monitor legislation and regulations that impact the company’s products and/or processes
• Update legal team with timely analysis and summaries of new legislation/regulations affecting the business
• Assist in developing automated processes for tracking regulatory changes and deadlines.

Insurance Regulatory Paralegal

Financial Planning and Analysis

• Serve as the trusted advisor and primary interface for leadership in Finance Operations function.
• Ensure IT investments and initiatives are directly aligned to Finance strategy and business goals.
• Build trust and foster strategic dialogue between Finance and Technology.
• Capture, elicit, and document Finance business requirements with precision and clarity.
• Translate business needs into actionable requirements, ensuring alignment with enterprise architecture.
• Hand-off requirements to technical delivery teams, while continuing to provide input and act as the business voice during design and build.
• Own and manage Finance products and capability roadmaps, ensuring priorities are visible, sequenced, and achievable.
• Define Finance capabilities, processes, and models to create a blueprint for aligning initiatives with enterprise strategy.
• Own all business outcomes delivered by BSGIT for Finance Operations function in Finance.
• Partner with delivery teams to ensure delivered solutions provide measurable business benefit.
• Act as the primary interface with Finance leadership, ensuring business needs and priorities are consistently represented.

Business Engagement Lead – Finance Operations

• Lead analytics and investigations that help the business understand exposure patterns and accumulation risk
• Define and enforce data standards, quality controls, and best practices for exposure data across business lines
• Own data quality and completeness - you not only collect feedback, but intuit what needs to be fixed from your industry experience, and collaborate with other departments on permanent solutions to reliably produce best in class exposure data
• Lead the oversight into ingestion, transformation, and normalization of exposure data from internal and external sources
• Validate and QA exposure data: identify anomalies, gaps, duplicates, inconsistencies, and drive improvements
• Partner with actuarial, underwriting, catastrophe modeling, and product teams to understand their exposure needs
• Develop and maintain exposure data documentation, data dictionaries, and process guidelines
• Enable and support analytical use cases (e.g. accumulation risk, portfolio stress testing, scenario analysis)
• Build, monitor and track data quality KPIs, build dashboards or alerts to surface issues proactively
• Support ad hoc analysis to diagnose exposure trends and concentration risk
• Provide guidance on integrating exposure data into downstream tools (e.g. modeling engines, pricing systems, BI)

Exposure Data Manager

Solutions Engineer

• Sit inside delivery teams for the duration of engagements, not alongside them
• Attend design and development sessions, review technical decisions as they are being made
• Continuously assess whether what is being built conforms to Accelerant's architecture principles
• Propose better paths and help the team take them where documented patterns do not exist
• Make sound technical decisions quickly with available information
• Assess capabilities built by business users and create a clear path to production
• Design and validate integration patterns between enterprise systems and data platforms
• Collaborate with the Data Office to ensure data products are accurate and accessible
• Document technical decisions and ensure architectural decision records exist and are accessible