Jobs — Novacture
Open positions
Final year internship (6 months) — Full-Stack Engineer | Actuarial SaaS Platform<
Novacture is modernizing its actuarial production platform into a multi-tenant SaaS. The internship focuses on building core business features to operate and commercialize the platform as a service.
Technical objectives
- User management: authentication, RBAC (Admin/Analyst/Reader), organization workspaces
- Subscriptions: entitlements, usage tracking, plan quotas/limits
- Multi-tenancy: data isolation, invitations/permissions, per-org configuration
- Security & compliance: audit logging, rate limiting, 2FA, GDPR features (export, right to be forgotten)
- Application infrastructure: real-time notifications, dashboards, webhooks, admin panels
- Plugin system: extensible architecture for modular SaaS features
Tech stack
- Frontend: React/Next.js, TypeScript, Tailwind CSS
- Backend: FastAPI (Python), PostgreSQL, Redis, Firebase
- Infra: Docker, Kubernetes, Scalingo, CI/CD (GitHub Actions, SonarCloud)
Required skills
- Python/FastAPI and REST API design
- Relational data modelling (SQL)
- Git, testing, maintainable & documented code
Nice to have
- DDD, Clean Architecture, CQRS
- TDD (frontend & backend)
- DevOps & Cloud, containerization
- AuthN/AuthZ (JWT, OAuth, RBAC)
- Multi-tenant SaaS & modular systems
Mission
- Functional analysis & DDD-driven design
- Iterative development, code reviews, pair programming
- CI/CD pipelines & continuous delivery (Scalingo)
- TDD, refactoring, documentation
- UAT, production rollout, knowledge transfer
Desired profile
- Final-year engineering school or MSc in Computer Science
- Strong interest in SaaS & product-oriented development
- Autonomy, rigor, end-to-end ownership
Perspectives
- Distributed computing orchestration, ML/AI integration
- Event-driven architectures, cloud-native migration
- New analytical components
Conditions
- Paid internship (depending on profile)
- Partial remote possible
- Individual technical mentoring
- Potential full-time offer
Application
- Resume, GitHub/portfolio, short cover letter
- Interview: show and explain code from a project
Final year internship (6 months) — Term Life / Credit Life Pricing & Modelling<
Build an end-to-end modelling framework for Term Life / Credit Life: mortality & early repayments, pure & commercial premium, and IFRS 17 provisioning — full Python development.
Academic goal
- Model mortality and early repayment intensities
- Build age × duration pricing bases
- Compute pure and commercial premiums
- Project cash-flows for IFRS 17 (LRC/LIC) & Risk Adjustment
- Document a replicable & automatable framework
Scientific approach
- Structure & clean loan-borrower data
- Explanatory modelling of intensities
- Construct & validate age × duration tables
- Sensitivity & robustness analyses
- Industrialize Python modules & reproducible scripts
IFRS 17 & evaluation
- Validation on historical data
- Transposability to IFRS 17 closes
- Deliverables compatible with actuarial reporting
What you’ll do
- Focused literature review
- Design the projection & pricing modules
- Develop a Python prototype
- Testing, sensitivities, validation & presentation
Profile
- MSc in Actuarial Science / Statistics / Data Science
- Strong Python (pandas, numpy, scikit-learn) and good Excel
- Rigor, analytical mindset, interest in IFRS 17
Final year internship (6 months) — ALM Modelling for Universal Life (Unit-Linked, Middle East) under IFRS 17 (VFA)<
Design and test an ALM model under the physical measure (P) for a UL portfolio (with COI): market projections, UL mechanics, dynamic policyholder behavior and VFA. 100% Python.
Academic goal
- Project equities, rates & spreads under P (best-estimate)
- Model UL mechanics and asset–liability feedbacks
- Estimate stochastic Best Estimate & sensitivities
- Improve VFA algorithm (entity share)
Scientific approach
- Market models under P & term-structure
- Portfolio management & rebalancing rules
- UL mechanics (account value, fees, COI, surrenders, deaths)
- Dynamic policyholder behavior
- ALM–liquidity coupling, VFA entity share
Evaluation & IFRS 17
- Empirical calibration & diagnostics
- Numerical stability & mass conservation
- Sensitivity & stress (volatility, spreads, liquidity, behavior)
- Targeted IFRS 17 reading (BE under P, VFA)
What you’ll do
- Focused literature review
- Parameterize an existing ESG
- Develop an asset–liability projection engine
- Behavior calibration, Monte Carlo simulations, analyses
Profile
- MSc Actuarial/Financial Engineering/Statistics
- Strong foundations in stochastic processes & portfolio management
- Advanced Python; interest in IFRS 17 (VFA)
Final year internship (6 months) — Modelling Decennial Liability Claims (Middle East) under IFRS 17<
Modernize claim emergence projections for a large decennial liability pool: segmented incidence law, 10-year emergence profile and IFRS 17 integration.
Academic & operational objectives
- Segmented incidence by construction characteristics
- Decennial emergence profile (non-uniform)
- Activation timing & residual delays for overdue policies
- Integration with IFRS 17: LRC cash-flows & Risk Adjustment
Methodology
- Risk & ruin theory (Cramér–Lundberg, Sparre Andersen)
- Collective GLM (frequency–severity)
- Survival methods (KM, CQR, AFT, Cox)
- Machine learning (gradient boosting incl. quantile) for comparison
- 10-year emergence vector & sensitivity analysis
IFRS 17 integration
- Calibration & information criteria, cross-validation
- LRC projection & Risk Adjustment
- Quarterly closes: AoC & experience variances
Profile
- MSc in Actuarial Science / Statistics / Data Science
- Probability, risk theory, survival models
- Scientific Python programming, methodological rigor
Open application
Don’t see the exact topic you want? Send us a short open application (resume + a few lines).
Open application at NovactureE-mail : admin@novacture.com