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ΠΎΠ±Π½ΠΎΠ²Π»Π΅Π½ΠΎ 13 Π΄Π½Π΅ΠΉ Π½Π°Π·Π°Π΄

Senior Data Scientist (Fraud Analytics)

Π€ΠΎΡ€ΠΌΠ°Ρ‚ Ρ€Π°Π±ΠΎΡ‚Ρ‹
hybrid
Π’ΠΈΠΏ Ρ€Π°Π±ΠΎΡ‚Ρ‹
fulltime
Π“Ρ€Π΅ΠΉΠ΄
senior
Английский
c1
Π‘Ρ‚Ρ€Π°Π½Π°
Bulgaria

ОписаниС вакансии

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TL;DR
Senior Data Scientist (Fraud Analytics): Building fraud detection, digital trust, and risk decisioning solutions on the Ascend platform with an accent on machine learning, graph analytics, behavioral intelligence, and GenAI. Focus on developing scalable fraud models and pipelines, transitioning prototypes into production, and validating model performance, fairness, explainability, and stability.

Location: Sofia, Bulgaria; hybrid remote/in-office

Company

hirify.global is a global data and technology company delivering data-driven solutions across financial services, healthcare, automotive, insurance, and other markets.

What you will do

  • Research and develop fraud analytics, digital trust, risk decisioning, device intelligence, behavioral intelligence, and GenAI solutions.
  • Analyze large-scale fraud, credit, device, behavioral, and digital-interaction data to identify risk and trust signals.
  • Develop fraud models, scores, attributes, device profiles, graph-based capabilities, and analytical tools for the Ascend platform.
  • Build scalable data pipelines, automation templates, and production-ready solutions while transitioning prototypes into production or client use.
  • Validate model performance, stability, fairness, explainability, and business value.
  • Lead analytical and productization workstreams, communicate technical recommendations, collaborate across distributed teams, and mentor colleagues.

Requirements

  • 5–7+ years of relevant experience in data science, AI, predictive modeling, or advanced analytics, including complex hands-on innovation and client-focused projects.
  • 7+ years of experience developing data and automation pipelines and moving analytical prototypes into monitored, scalable production solutions.
  • Strong knowledge of probability, statistics, optimization, linear algebra, calculus, model validation, and advanced machine learning methods.
  • Near-production-level Python, plus experience with PySpark and distributed data processing.
  • Knowledge of large-scale data technologies, cloud platforms, NoSQL and graph databases, time-series data, unstructured data tools, and LLM or agent-based development frameworks.
  • Fluent English and an advanced technical or quantitative degree, or equivalent experience.

Culture & Benefits

  • Flexible working hours and home-office options within the hybrid arrangement.
  • Professional development programs, career pathways, and access to online courses, learning materials, and books.
  • Social benefits including life and additional health insurance, food vouchers, flex allowance, internet coverage, corporate discounts, and a Multisport card.
  • 25 days of paid vacation, a birthday day off, and three additional paid days for social responsibility activities.
  • Friendly working environment, team activities, employee assistance program, Sharesave plan, and family-related allowances.