Fraud-Detection Data Scientist — Hybrid Work & Growth

Prima; Milan (IL); Hybrid; USD 80,000 - 120,000; Full time

Benefits offered by this job

Private healthcare

Gym discounts

Wellbeing programs

Mental health support

Flexible working (remote/hybrid)

Job summary

Prima is seeking a skilled data scientist to enhance fraud detection systems that prioritize high-risk claims. You'll collaborate with cross-functional teams, developing insights into fraud dynamics and improving operational efficiency.

Ideal candidates will have extensive experience in data science, strong analytical skills, and proficiency in Python, Spark, and SQL. Enjoy hybrid work options and comprehensive benefits, including private healthcare and learning resources.

Qualifications

• 3+ years of experience in data science or applied machine learning.
• Strong analytical and quantitative mindset capable of translating data into insights.
• Skilled in problem-solving and defining success metrics.
• Proficient in Python programming for data analysis.
• Knowledge of data-oriented languages, Spark, SQL, and relevant libraries.

Responsibilities

• Design and improve fraud detection systems for high-risk claims.
• Collaborate with fraud analysts, engineers, and product managers.
• Develop expertise in fraud dynamics and identify emerging fraud patterns.

Skills

Data science experience

Quantitative analysis

Problem-solving

Python programming

Knowledge of Spark

SQL proficiency

Experience with data libraries

Tools

Git

Pandas

Sklearn

Keras

XGBoost

LightGBM

Job description

Prima is seeking a skilled data scientist to enhance fraud detection systems that prioritize high-risk claims. You'll collaborate with cross-functional teams, developing insights into fraud dynamics and improving operational efficiency.

Ideal candidates will have extensive experience in data science, strong analytical skills, and proficiency in Python, Spark, and SQL. Enjoy hybrid work options and comprehensive benefits, including private healthcare and learning resources.