Citi’s Innovation lab in Tel Aviv is a greenhouse for start-up like products within the Fintech industry. We deliver innovative products using cutting-edge technologies in highly complex architectures and with the highest delivery standards. We work on projects in many advanced domains spanning across AI, Machine Learning, Big Data, NLP, Analytics, Blockchain and many more.
The data scientist will take part in the implementation of new and strategic initiatives, and will focus data related tasks applying data science and algorithmic solutions. The ideal candidate has experience in solving analytical problems using quantitative approaches, a passion for data, enthusiasm to work closely with business partners on data-related projects and background in finance. This is a unique opportunity to initiate and drive data-driven projects with high business impact and visibility within a large financial organization.
- Formulate financial business use cases in machine learning terms
- Define tests and experiments that aim to assess the relevancy and feasibility of machine learning solutions to business use cases
- Assess data availability and data quality
- Understand our data and apply techniques for feature engineering and selection
- Apply state-of-the-art machine learning techniques to financial data such as model selection, training, testing and validation
- Compile and present complex information using data visualization tools such as interactive notebooks or single-page application
- Prepare and present written and verbal reports to key stakeholders
- Work closely with product owners to develop client solutions for new and existing channels
- Establish effective working relationships directly with your stakeholders
- Grow our catalogue of common assets, such as code templates, libraries, utilities, services, etc.
Experience & Qualifications
- B.Sc Mathematics/ Economics/ Computer Science / Statistics or equivalent
- At least3 years of experience as a data scientist
- You must be highly proficient in Python and relevant libraries
- Knowledge of a variety of machine learning techniques (exploratory data analysis, predictive modeling, supervised/unsupervised machine learning, anomaly detection) and their real-world advantages/drawbacks – Must.
- Background in finance is a strong advantage
- Experience with data visualization tools – an advantage
- Passionate about financial data and problem solving. Understand that financial data comes in different formats and sizes.
- Proficiency in using query languages, such as SQL, Spark DataFrame API, etc. – an advantage
- Experience with Deep Learning, particularly when applied to financial data – an advantage
- You should know how to balance between theory and practice
- Self-motivated and team player that has the drive to learn and master new technologies and techniques.
- You are an excellent communicator, able to explain your work in layman’s terms
- You are eager to grow your skills.
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