לוח משרות דרושים Data Scientist בירושלים

Requirements:
* Bachelor's degree in Statistics, Mathematics, data Science, Economics, or a highly quantitative field - Must (Advanced degree an advantage)
* 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 A Bonus
* Experience with Fair Lending analytics preferred
* Familiarity with Fair Lending regulations such as the Equal Credit Opportunity Act (ECOA), Fair Housing Act (FHA), and Home Mortgage Disclosure Act (HMDA) or other consumer financial protection laws and regulations preferred
* Experience in the financial service sector including lending products or credit risk management preferred
* Experience with data visualization tools such as Tableau and Power BI an advantage
* Experience with Machine Learning techniques, such as decision trees, random forests, or gradient boosting an advantage.

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 - Must (Advanced degree an advantage)
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
A Bonus:
Experience with Fair Lending analytics preferred
Familiarity with Fair Lending regulations such as the Equal Credit Opportunity Act (ECOA), Fair Housing Act (FHA), and Home Mortgage Disclosure Act (HMDA) or other consumer financial protection laws and regulations preferred
Experience in the financial service sector including lending products or credit risk management preferred
Experience with data visualization tools such as Tableau and Power BI an advantage
Experience with machine learning techniques, such as decision trees, random forests, or gradient boosting an advantage.

Requirements:
M.Sc or Ph.D. degree in a technical field from a top tier university or equivalent experience.
4+ years of experience in leading machine learning related projects (e.g. recommendation systems, search, natural language processing, large language models).
Experience with deploying machine learning models to production.
Python experience & SQL skills - a must.
Demonstrated ability to generate new ideas and innovate.
Research track record including main contributions to projects you can showcase, peer-reviewed research publications, etc.

Requirements:
3+ years of experience as a data scientist in the industry, experience from b2c companies is a plus.
High communication skills, understanding business needs, and combining the business case into the data science area in order to leverage decision making.
Deep understanding of classical ML & DL algos for a wide spectrum of problems and domains. Time series modeling - must.
MSc or PhD in Computer Science, Data Science, Statistics or a related field.
Proven hands-on experience developing and researching algorithms in various fields and data science/machine learning techniques such as: boosting algorithms, time series models, clustering, anomaly detection methods, and more.
Proven experience in taking projects through all the stages of a new ML model, from data analysis and labeling to prototyping, implementation in a production environment, and monitoring and maintenance. Delivery oriented.
Proficiency with Python and SQL.