דרושים » תוכנה » Senior Data Scientist

As a Data Scientist, you will work in a highly collaborative environment with extensive amounts of data to research and develop deep learning models to solve real-world problems and apply them to key risk department initiatives such as predictive spam detection, performance forecasting, and identifying bad actors by using machine learning models.

Connecting people across the world is a complex problem with many machine-learning applications. The purpose of this role is to implement models and algorithms to solve complex business problems in risk & fraud domains. Successful outcomes will significantly impact our hundreds of millions of daily active users around the globe.

Responsibilities:
Work with management and partner teams to design and implement solutions for given objectives.
Commitment to success metrics, ensuring low FP, and accurately measuring the impact and model performance.
Lead technical efforts to improve the performance of our Risk & Fraud models and propose initiatives in that domain to shape our long-term risk-mitigation vision.
Autonomously find solutions to complex data problems and understand the data generation process and the challenges with the data.
Leverage the extensive data received from our application to enhance model performance and accuracy.

We are looking for a highly motivated candidate to join our Data Science team If you are passionate about NLP \LLMs and have 4+ years in the field, this is for you!

What Youll Do:
Research, experiment, develop and productize advanced NLP, LLM and autonomous agent solutions in various domains such as classification, summarization, translation, information retrieval and AI assistant.
Use advanced deep learning and large language models, to enhance Shields ability to find the needle in a haystack in the world of structured & unstructured data of financial electronic communication.
Conduct rigorous experimentation, analysis, and optimization to ensure performance, efficiency, and scalability.
Develop processes, tools and frameworks to monitor and analyze model performance and data accuracy.
Innovate, develop, and test state-of-the-art approaches to solve our challenging problems: domain adaptation, fine-tuning, prompt engineering, zero- and few-shot learning, autonomous agents, using open and close large language models.
Assist and mentor other team members in the implementation and research.
Collaborate closely with domain experts, product and engineering teams to translate research breakthroughs into scalable commercial products.
Identify the latest technology to improve our AI capabilities in a variety of languages and help shaping our AI roadmap.