Fraud Analyst

Job description

About Snapp

Snapp is the pioneer provider of ride-hailing mobile solutions in Iran that connects smartphone owners in need of a ride to drivers who use their private cars offering transportation services. We are ambitious, passionate, engaged, and excited about pushing the boundaries of the transportation industry to new frontiers and be the first choice of each user in Iran.

About Fraud team

Here in Snapp Group, we should make data-driven decisions. Using data analysis and artificial intelligence science, we identify various fraud. the Fraud team typically operates in a variety of areas including Transportation, Food, Shopping, Travel, FinTech, FMCG and the Health market.

Responsibilities

We are looking for a fraud analyst who helps us discover the information hidden in vast amounts of data, and helps us make predictive models to deliver even better products. Your primary focus will be on applying machine learning techniques, doing statistical analysis, and building high-quality prediction systems integrated with our products.

Requirements

  • Knowledge and experience of the Python Libraries: Pandas, NumPy, SciPy, StatsModels, scikit learn, Seaborn, and Matplotlib.
  • Knowledge and experience in image processing and NLP is a plus.
  • Knowledge and experience in Linux/ubuntu server is a plus
  • Familiar with machine learning techniques and algorithms, such as SVM, Decision Forests, Linear Regression, Logistic Regression, Decision Tree, Random Forest, etc.
  • Strong understanding of machine learning techniques and algorithms.
  • Advanced SQL knowledge and experience working with both relational and non-relational databases, query authoring as well as working familiarity with a variety of other databases and datasets.
  • Understanding the model build life-cycle, including feature selection and optimization, model selection and validation, and ongoing model maintenance..
  • Skilled in reporting
  • Confidence, supported by a proactive approach to work
  • The ability to analyze complex issues
  • Problem solvers
  • People who are inspired by working in a collaborative professional environment
  • The hunger to grow and the ability to learn quickly