Python Numerical Computing Engineer

Overview

Akur8 is a fast-growing Insur Tech scale-up on a mission to modernize how insurers assess, price, and manage risk. Our next-generation SaaS platform combines transparent machine learning, predictive analytics, and smart product design to turn complex insurance workflows into scalable, data-driven systems. Powered by expert engineering, data, product, and actuarial teams, Akur8 enables insurers to model risk up to 10x faster while maintaining transparency, explainability, and regulatory trust.

As our product suite expands, we are building an end-to-end platform supporting pricing, reserving, and forward-looking risk decisions — helping insurers operate efficiently in a complex environment. Recognized Globally, Akur8 Has Been Featured In CB Insights’ Insurtech 50 (2025), CNBC’s Insur Tech Top 150 (2025), Insur Tech
100 Global Insurtech Top 100 (2025), Professional Equality Index 97/100 (2025). With 40+ nationalities across 8 global offices, we serve 320+ clients across 4 continents while maintaining a strong engineering and product culture. We are proud to be an equal opportunities employer, fostering an inclusive environment where diverse perspectives help shape better products and decisions.

• Translate actuarial requirements (including prototype R code) into efficient, maintainable Python
• Optimize complex mathematical operations to run 10× faster using vectorization and algorithmic improvements
• Implement and refactor numerical Python functions with performance and correctness in mind
• Profile and improve existing codebases handling large analytical workloads
• Build reusable numerical utilities to support actuarial analysis and diagnostics
• Optimize computational bottlenecks in insurance reserving models
• Collaborate closely with actuaries and subject-matter experts
• Write clear, robust unit tests for numerical logic and edge cases

NUMERICAL COMPUTING

• Implement domain-specific technical specifications using Num Py as the primary numerical tool
• Translate written requirements and mathematical definitions into efficient, testable implementations
• Apply vectorization and, where relevant, parallelism to process large data volumes
• Ensure numerical results can be returned to calling services at speeds as close to real-time as possible
• Actively participate in code reviews, providing and incorporating feedback with a focus on correctness, performance, and clarity

DATA & STORAGE

• Work with relational databases (e.g. Postgre
  
  SQL) and/or No
  
  SQL-style data
• Confidently handle JSON-based data structures
• Use Polars or Pandas for structured data manipulation and analysis
• Translate between data representations as required (e.g. numerical matrix ↔ relational-style table ↔ dictionary / JSON)
• Collaborate with peers to review data modeling and transformation approaches

STATISTICAL & REPORTING TOOLS (Supporting Role)

• Implement statistical models using Stats models for modeling and diagnostics (secondary focus)
• Use Scikit-learn for ML workflow fundamentals (pipelines, metrics, validation — not core ML research)
• Review and validate statistical and analytical implementations with peers to ensure correctness and maintainability

ENGINEERING PRACTICES (CROSS-CUTTING)

• Implement features based on clear technical specifications and acceptance criteria
• Write readable, maintainable code that supports effective peer review
• Engage constructively in code reviews, both giving and receiving feedback
• Ensure implementations are well-tested and aligned with agreed technical designs

TECHNICAL ENVIRONMENT

• Python (core language)
• Num Py, Polars / Pandas for numerical computing and data manipulation
• Stats models, Scikit-learn (supporting analytical tooling)
• Postgre
  
  SQL, JSON-based data storage
• AWS
• Wider company stack includes C#, .NET, Angular, Kubernetes

ENGINEERING WORKFLOW

• Git Hub for version control, pull requests, and code review
• Jira for work tracking and delivery
• Confluence for technical documentation and shared specifications
• Engineers write clear commits and pull requests that are easy to review
• Engage in peer code reviews and ensure ticket status is up to date

• 3+ years of experience using Python for numerical computing
• Proven…