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Statista

Global data platform for market research

Senior Backend Engineer - Scoring & Computation Engine

Backend EngineeringConfirmed live in the last 24 hours
Full-timeNo salary listed

About the Job

Requirements

  • Deep expertise in modeling and evaluating expression trees and dependency graphs, including abstract syntax trees, directed acyclic graphs, cycle detection, topological sorting, memoization, and selective recomputation.
  • Mastery of modern Python with strict typing using mypy or pyright, explicit testing discipline, and clean packaging practices.
  • Proven experience building auditable, reproducible systems using immutable execution records, versioned schemas, and explicit data lineage tracking.
  • Experience treating business logic as versioned data, such as typed schemas, expression trees, rules engines, or domain-specific configurations.
  • Demonstrated ability to design, version, and operate production backend contracts and schemas for upstream workflow engines and downstream applications.
  • Bachelor's or Master's degree in Computer Science, Software Engineering, Applied Mathematics, or a related quantitative field.
  • At least 5 years in backend software engineering building computation engines, rules platforms, or complex data-intensive backend systems, including a sustained period within one organization seeing a core system through build, launch, and iteration.
  • A strong analytical and mathematical mindset, with the ability to translate complex domain logic and formulas into clean, deterministic software abstractions.
  • Fluency in English.
  • A highly structured, detail-oriented working style and motivation to collaborate closely with methodology experts, analysts, and cross-functional engineers in an international environment.

Responsibilities

  • Design and build the core scoring engine as a typed, versioned computation graph executed deterministically with clear boundary contracts.
  • Model complex business logic—including formula trees, categorical mappings, peer selection, and comparability adjustments—as versioned, declarative data structures.
  • Own system lineage, versioning, and execution auditability end-to-end, ensuring any score can be recalculated identically at any future date.
  • Build clean, typed services and contracts for the internal methodology workbench and downstream consumer applications.
  • Establish rigorous testing practices, such as golden file testing, property-based testing, and regression validation, to prevent calculation drift.
  • Shape architecture, drive trade-offs between execution speed and cost, set code review standards, and mentor joining engineers.

Desired Qualifications

  • Production experience with FastAPI or similar asynchronous frameworks and workflow tools such as Dagster, Prefect, or Airflow.
  • Practical experience analyzing execution memory footprints, CPU profiles, or query efficiency against columnar data warehouses.
  • Familiarity with deploying, monitoring, and operating containerized calculation microservices on AWS.
  • Healthcare or benchmarking domain experience, including basic understanding of healthcare key performance indicators, quality metrics, or benchmarking concepts; familiarity with hospital rating systems, medical classification, or complex scoring methodologies is especially valuable.
  • German language skills.

About the Company

Statista

Global data platform for market research

Statista is a global data platform that collects and curates statistics from more than 22,500 sources across 170 industries and 50 countries. It serves businesses, universities, and governments by offering high-quality statistics, infographics, and studies through a subscription-based model, API access, and customized research projects. The platform is updated regularly to ensure current insights, with some updates following major industry events. Users access the data via a subscription, API, or bespoke research services to obtain market insights and revenue information. Compared with competitors, Statista combines a vast, cross-industry data catalog with easy-to-use visualizations and tailored research options, enabling organizations to obtain global insights efficiently. The company’s goal is to help clients across sectors make data-driven decisions by providing reliable, accessible market statistics and analysis.

Company size
1,001-5,000
Company stage
Acquired
Total funding
$62.9M
Headquarters
New York City, New York
Founded
2007

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