Data Scientist

A Fintech company that has developed technological infrastructure in the financial sector, offering real-time solutions in the areas of payments, credit cards, loans, and more. They have raised $620M at a valuation of $3.5 billion.

The company promotes equal opportunities and diversity (e.g., about 43% women in the Israeli site), is experiencing growth, and intends to continue being at the forefront of financial innovation emerging from Israel and driving the global economy's infrastructure.

They offer excellent welfare conditions such as career development paths, private health insurance, work-life balance, a continuing education fund beyond the tax ceiling, and more.

Located in Jerusalem, they offer a hybrid model of three days working from home. The company has 900 employees worldwide, with 180 in the R&D center in Israel.

Role Description: Working as part of a team in Data Science and classic ML models—both theoretical and engineering—including working with Classification, Random Forest, KNN, Regression, Gradient Boosting, SVM, Predictive models, Statistical modeling, AWS, SageMaker, Large Scale, coding in Python, R, and SQL, and working with tabular data in the financial sector.

Requirements-

• Proficient in Hebrew and English both written and verbal, sufficient for achieving consensus and success in a remote and largely asynchronous work environment - Must

• Bachelor's degree in Statistics, Mathematics, Data Science, Economics, or a highly quantitative field

• 3 years of experience in data analysis, statistical modeling, and predictive analytics within the financial services industry, preferably in Fair Lending or credit decisioning

• Strong technical proficiency in data science tools and programming languages such as Python, R, SQL, with experience in developing predictive models and machine learning algorithms.

• Strong knowledge of advanced analytics and machine learning techniques such as Regression and Classification algorithms, including linear and logistic regression, random forest and gradient boosting, k-nearest neighbors, support vector machines (SVMs) and other techniques

• Experience working with cloud-based data platforms and technologies such as AWS and Sagemaker for scalable data analytics and machine learning

• Experience working with large-scale datasets

• Ability to communicate findings and recommendations to stakeholders

• Strong problem-solving skills while paying attention to detail

• Ability to work independently and collaboratively in a fast-paced environment, managing multiple projects and priorities simultaneously

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