דרושים » תוכנה » Mid-Senior Data Scientist - Image Analysis, Computer Vision, and Text Reading

We are looking for a Data Scientist to join our team.

The ideal candidate is a highly motivated and self-driven individual with strong analytical and problem-solving skills. The Data Scientist will be responsible for analyzing data and developing models to help inform decisions and strategies for new products and business initiatives.


Responsibilities:
Work closely with stakeholders to understand business requirements and develop predictive models to detect fraud.
Develop and implement statistical models, machine learning and deep learning algorithms to solve complex problems in a production environment.
Perform exploratory data analysis and data visualization to gain insights and communicate findings.
Collaborate with cross-functional teams, including data engineers and software developers, to design and implement end-to-end solutions that can be deployed in production.
Implement advanced analytics tools and technologies to enhance reporting capabilities.

we are looking for a Data Science Team Lead.
The Data Science department plays a pivotal role in our company, generating value by developing algorithms and analytical production-grade solutions. We leverage advanced techniques and algorithms to extract maximum value from data of all shapes and sizes, including classification models, NLP, anomaly detection, graph theory, deep learning, and more.
Our models and algorithms are integrated into the critical path of product, helping to make thousands of decisions per second in real-time. All the capabilities we develop must meet production-grade requirements in both analytical and engineering standards.
As the Team Lead of a Data Science team, you will manage critical analytical initiatives for our suite of products, shaping the team's direction and focus. You will collaborate closely with Product Managers to influence the future of our product offerings and ensure alignment with company goals. You will need a holistic view of challenges and a keen understanding of the underlying goals of the department and company. In this role, you will lead the team, oversee their professional development, build effective collaborations with other departments, and bring measurable value to product through your team's efforts.

Were looking for a Data scientist Expert to join us and spread our power. As a Data Scientist you will be responsible for driving research and development of autonomous AI agents and LLM-powered systems. You will work closely with cross-functional teams to explore, innovate, and implement AI-driven solutions to tackle emerging threats, examine cloud security features, and enhance the companys security posture.
WHAT YOULL DO
Lead applied research on AI agents and LLM-driven features in the platform - from autonomous threat investigation agents to AI-powered security operations workflows
Cover a range of features - from leveraging LLMs to enhance customer investigation experience to novel usage of AI for cloud security
Collaborate with engineering teams to design, build, and maintain production pipelines
Work closely with the Security Research and Product teams to define research goals
Conduct experiments and evaluate the performance of AI models, algorithms, and techniques using real-world datasets and simulated environments
Stay abreast of cutting-edge AI methodologies, frameworks, and tools and apply them to improve security solutions' accuracy, efficiency, and scalability.

we are looking for an experienced, independent team player who has great data & computer science skills, a passion for data, and excellent analytical and algorithmic skills.
This role is diverse, encompassing AI/ML, data analysis, and backend engineering.
You will play a crucial role within a mission-critical team responsible for managing the heart and brain of primary products. This involves working on core systems, such as POS underwriting models, models for merchant operations, Fraud investigator AI agents and more.
You will participate in cutting-edge risk management systems that safeguard the loan product's financial operation, as well as operational systems, with a direct impact on its financial success.
Our AI/ML team is part of the R&D group, so you will work closely with engineers and product managers as well.
Key Responsibilities
Research and develop statistical behaviors, study domain-specific data.
Develop state-of-the-art machine learning models end to end, including development, deployment, and continuous improvement. Both in-weight learning and in-context learning, for risk / fraud / operations related projects. This includes integrating models into production services and ensuring compliance with regulatory processes (e.g. providing evidence for production model audits).
Operate backend infrastructure for training and deploying ML models, ensuring optimal performance and reliability.
Develop and maintain Python code for translating ML model outputs into financial decisions.
Analyze 15+ different data sources in order to train models and agents to catch fraudulent patterns.
Conduct analytical research on our models impact on the portfolio.
Strategize and implement changes to enhance portfolio performance.

As a Senior Data Scientist on Research team, youll develop and productionize ML/AI models that power our classifications and insights. Youll partner closely with Product and Engineering to turn open-ended data-security challenges into measurable experiments and shipped features. Youll own the end-to-end lifecycle-from problem framing and data strategy to evaluation, deployment, and ongoing monitoring-helping customers discover, protect, and govern their data at scale.



What Youll Do

Responsibility for an end-to-end research process. That includes identifying the problem, feature engineering, model development to deployment, outcome analysis, and refinement.
You will be a hands-on domain leader, laying the foundations of our data science workflows and algorithms. This is an excellent opportunity to work with endless amounts of user data and creatively generate insights that will increase the ability to classify tons of data.
Develop, evaluate, and maintain machine learning and NLP solutions to enhance core capabilities in sensitive data classification.
Innovation and creative thinking are the keys! Implementing ML models to the entire research process - clustering, text extraction, document analysis, and tabular data classification.
Close interaction and collaboration with an excellent team of engineers, data analysts, and security researchers.

We are looking for a passionate Senior Data Scientist to join our all-star team. This is an amazing opportunity to join a multi-disciplinary A-team while working in a fast-paced, results, marketing and data-oriented environment. If you are experienced but still hungry to learn and impact - wed love to have you on our team!

What Youll Do:
Devise, initiate, manage and execute cutting-edge exploration and exploitation projects.
Apply your knowledge of Data Science, Machine Learning and AI-driven algorithms to create scalable data solutions.
Analyze extremely large (petabytes) and diverse datasets to solve complex problems, and develop automated, intelligent systems to address them.
Design, build and deploy AI/ML models (including predictive models, recommendation systems and generative AI solutions) to drive business impact.
Leverage modern AI tools and frameworks to accelerate research and production workflows.
Proactively seek growth opportunities aligned with core KPIs.
Enable real-time and near real-time data insights - instant data gratification guaranteed.

We seek a highly skilled and motivated Data Operations Specialist to join our data annotation team.

In this role, you will support a team of data annotation experts, ensuring the accuracy and reliability of annotated data. This role involves hands-on data annotation and tagging, integrating advanced technologies to streamline data operations, and collaborating with various departments to achieve organizational goals.

A day in the life and how youll make an impact:

Perform data annotation and tagging tasks as needed, maintaining high standards of accuracy and quality.
Utilize cutting-edge technologies and tools to enhance data operations, improving annotation capabilities and overall project efficiency.
Conduct performance reviews of third-party vendors and in-house team members to ensure alignment with project goals and adherence to high-quality standards.
Oversee multiple concurrent projects, working collaboratively with various departments to meet project milestones and organizational objectives.
Partner with algorithm developers to bridge the gap between labeling concepts and technical constraints, ensuring effective communication and alignment throughout the project lifecycle.
Drive continuous improvement in data operations by optimizing workflows, creating automation solutions using Python, and implementing best practices to enhance efficiency and reduce manual effort.
Exceptional interpersonal skills with a strong ability to build relationships, integrate smoothly into the company culture, and foster team collaboration.
Service-oriented mindset with a high level of dedication to supporting both internal teams and external partners.

we are looking for a Junior Fraud Data Scientist.
As a Junior Fraud Data Scientist, you will contribute to our ongoing efforts to protect our ecosystem from financial threats and abuse. Working under the guidance of senior team members in a data-rich environment, you will assist in identifying malicious behaviors, support detection coverage, and help maintain our automated mitigation strategies.
This role is designed for an analytical professional with 1-2 years of experience who wants to build a deep expertise in adversarial data, learn from an experienced team, and develop their technical skills across modern cloud data platforms.
What You Will Be Doing
Exploratory Data Analysis: Support the team by mining behavioral and transactional datasets to help identify anomalies and emerging fraud patterns.
Model Support & Optimization: Assist in building, tuning, and validating machine learning models (e.g., XGBoost, LightGBM) under the supervision of senior data scientists.
Feature Generation: Extract, engineer, and prepare new data features from structured and unstructured sources to help improve model performance.
Dashboarding & Monitoring: Build and maintain internal dashboards and pipelines to track model health, data drift, and key fraud KPIs.
Cross-functional Collaboration: Work alongside Fraud Analytics and Product teams to help translate operational fraud insights into automated data solutions.

we are looking for a AI Solution Engineer.
The AI Solutions Engineer plays a critical, high-impact role in scaling our clinical AI solutions and ensuring the ability to deploy high quality products, monitor and support them in production.
This position requires strong software and data engineering skills to elevate our operational systems.
You will be responsible for independently driving complex E2E projects, demonstrating flexible thinking and making cost-effective decisions while balancing quality versus speed.
You will serve as a vital technical bridge, forming strong collaborations with both the R&D and Product organizations. Success in this dynamic and fast-driven environment demands a focused "getting things done" and "can-do" attitude to deliver value with speed and quality.
Responsibilities:
Automate and streamline AI operations - develop tools to automate AI deployment, data validation, and reporting for smooth production integration of AI solutions built by our research teams.
Act as the production technical expert - collaborate with Product and R&D teams during feature design to ensure production feasibility, scalability, and operational excellence.
Lead end-to-end tool development - gather requirements, design, implement, and deploy operational tools and pipelines in collaboration with cross-functional teams.
Drive engineering quality and play a key role in team member mentoring - uphold and develop engineering standards while fostering innovation.
Investigate and resolve complex data challenges - analyze and address production data issues, including data quality, availability, performance anomalies, and integration challenges.
Collaborate with customer-facing teams - understand real-world operational challenges, develop scalable solutions, and bridge the gap between customer needs and AI system behavior.
Ensure ongoing AI model reliability - design and implement mechanisms for monitoring data and performance degradation, and maintaining long-term model effectiveness.
Develop monitoring and analytics frameworks - create metrics and dashboards to track production health, data integrity, and AI performance across the deployment lifecycle.

We are looking for an experienced Applied Data Scientist with expertise in building agentic systems and autonomous agents to join one of our R&D. You will be at the core of transforming our supply chain solutions into a fully agentic platform - designing and building agents that autonomously generate analytical pipelines, orchestrate multi-step reasoning, and resolve complex logistics challenges for our customers.
You will combine strong machine learning and deep learning expertise with the ability to architect and implement production-grade agentic systems, working closely with engineering, product, and domain experts to push the boundaries of what autonomous AI can do in supply chain.
Responsibilities:
Design and build autonomous agentic systems that generate, configure, and execute analytical pipelines to solve supply chain challenges end-to-end
Architect multi-agent workflows with planning, tool use, memory, and feedback loops - enabling agents to reason, adapt, and improve over time
Develop and integrate ML and deep learning models (e.g., predictive models, anomaly detection, demand forecasting) as core capabilities within agentic pipelines
Research and apply state-of-the-art techniques in agentic AI, LLM orchestration, and multi-agent systems to production use cases
Translate complex logistics and supply chain challenges into agent-based problem formulations, collaborating closely with product and domain experts
Define and implement rigorous evaluation frameworks for agent performance: correctness, reliability, robustness, and edge-case handling
Collaborate with software engineers to productionize agentic solutions - including testing, monitoring, versioning, and iterative improvement
Contribute to team practices: reproducible code, experiment tracking, documentation, and knowledge sharing