דרושים » תוכנה » Data Scientist

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 provide maximum value from data in all shapes and sizes (such as classification models, NLP, anomaly detection, graph theory, deep learning, and more). As a Data Scientist, you will assume the classic data-science role of an end-to-end project development and implementation practitioner. Being part of the team requires a mix of hard quantitative and analytical skills, solid background in statistical modeling and machine learning, a technical data-savvy nature, along with a passion for problem-solving and a desire to drive data-driven decision-making.
What You'll Be Doing
Data Exploration and Preprocessing: Collect, clean, and transform large, complex data sets from various sources to ensure data quality and integrity for analysis
Statistical Analysis and Modeling: Apply statistical methods and mathematical models to identify patterns, trends, and relationships in data sets, and develop predictive models
Machine Learning: Develop and implement machine learning algorithms, such as classification, regression, clustering, and deep learning, to solve business problems and improve processes
Feature Engineering: Extract relevant features from structured and unstructured data sources, and design and engineer new features to enhance model performance
Model Development and Evaluation: Build, train, and optimize machine learning models using state-of-the-art techniques, and evaluate model performance using appropriate metrics
Data Visualization: Present complex analysis results in a clear and concise manner using data visualization techniques, and communicate insights to stakeholders effectively
Collaborative Problem-Solving: Collaborate with cross-functional teams, including product managers, data engineers, software developers, and business stakeholders to identify data-driven solutions and implement them in production environments
Research and Innovation: Stay up to date with the latest advancements in data science, machine learning, and related fields, and proactively explore new approaches to enhance the company's analytical capabilities

We are seeking an experienced and visionary Data Scientist to join our dynamic technology organization. The successful candidate will be a part of a team of talented data scientists, driving innovation and delivering business value through advanced machine learning techniques and Generative AI solutions. This role requires a strategic thinker with hands-on expertise in both traditional and cutting-edge data science methodologies, and a passion for continuous learning and development.
Responsibilities:
Gradient boosting techniques (e.g., XGBoost, LightGBM, CatBoost) are used to enhance predictive accuracy and model robustness.
Drive the exploration and integration of Generative AI applications, including Large Language Models (LLMs), to create innovative solutions for our products and services.
Collaborate with cross-functional teams (engineering, product, business) to translate business requirements into actionable data science projects.
Establish best practices for model development, validation, deployment, and monitoring in production environments.
Promote a data-driven culture, encouraging experimentation, sharing of knowledge, and adoption of state-of-the-art technologies.
Communicate project progress, insights, and results to stakeholders at all levels of the organization. Design, implement, and optimize classic machine learning models to solve complex business problems.

We are seeking a talented and experienced team manager to head our Data Science team within the critical Risk domain. This role uniquely combines hands-on development of vital risk prevention models, team mentoring, defining the technological strategy, and driving innovation in the field of AI Agents.

Key Responsibilities
As the Data Science Team Lead for Risk, you will be responsible for:

Technological and Strategic Leadership: Defining and implementing the Data Science strategy for the Risk domain, while identifying critical business and technological opportunities.
Hands-on Development: Actively working on the development, building, and deployment of critical Machine Learning and Gen-AI models for identifying, classifying, and preventing risks and fraud.
Team Management and Mentoring: Managing and guiding a team of talented Data Scientists, including work planning, professional development, providing mentorship, and contributing to talent acquisition.
AI Agents Innovation: Leading the team's efforts in the field of AI Agents within Risk, including architectural design, developing complex Agent Workflows, advanced Prompt Engineering, and developing rigorous Evaluation methodologies to ensure reliability and accuracy in production.
Cross-Functional Collaboration: Managing strategic relationships and collaborations with Engineering, Product Managers, Analysts, and other stakeholders to ensure solutions meet critical business needs.
Production Deployment: Ensuring Data Science solutions transition reliably, scalably, and efficiently from concept to production and making significant impact.

We are looking for a strong, hands-on Data Scientist with knowledge in Security Research to join a cutting-edge AI and cyber security initiative .
In this role, youll be part of a growing data science team working on advanced prevention technologies, leveraging vast amounts of data and state-of-the-art machine learning techniques to help protect users on a global scale.
This is a unique opportunity to join a high-impact, research-driven environment, where you will have the chance to shape core components of a next-generation security solution.

Key Responsibilities
Research and develop innovative AI-powered capabilities for cyber threat prevention.
Perform hands-on malware analysis in Windows environments, focusing on files and related threats.
Rapidly prototype and iterate based on data insights and user feedback.
Design and build data-driven solutions with a strong emphasis on practical impact and performance.
Collaborate closely with cyber researchers, analysts, and engineers to deliver production-grade machine learning models.
Work across organizational boundaries to bring solutions from concept to large-scale deployment, considering system constraints and integration challenges.

We are seeking a talented and mission-driven Data Scientist to join our growing Data organization. As a Data Scientist, you will own complex, high-impact projects end-to-end from research and experimentation through production deployment and monitoring.
You will develop and refine the machine learning models that power our personalization engine, engagement optimization, and clinical insights. Your work will directly shape the way millions of people experience their healthcare and improve their well-being.
Responsibilities
Lead end-to-end development of machine learning models, from research, data exploration, and feature engineering to training, validation, deployment, and post-production monitoring.
Partner closely with product managers, data engineers, and software engineers to translate strategic questions and user behavior patterns into measurable, data-driven solutions.
Research, prototype, and implement cutting-edge ML, deep learning, causal inference, and reinforcement learning techniques to tackle complex healthcare challenges.
Contribute to ML infrastructure and tooling to ensure scalability, reliability, reproducibility, and performance across all production workflows.
Drive innovation by exploring new approaches in Generative AI, LLM-based systems, and AI-agent architectures to enhance recommendation, engagement, and personalization capabilities.
Design, execute, and interpret A/B tests and other experimental methodologies to rigorously measure the impact of new models, product features, and interventions.
Collaborate, mentor, and share best practices to elevate technical excellence across the Data Science discipline.

As a data scientist, you will work on the very core of the company. Part of your role will be to turn raw data into usable metrics and develop new models and statistical algorithms to support our business. Together with other Data Engineers and Product Managers, you will translate the voice of our customer into best-in-class digital insights.

Responsibilities:
Analyzing data from various sources and transforming it into actionable insights that directly drive business growth.
Building machine learning algorithms for bidding - using classification and clustering to optimize campaign performance.
Leveraging artificial intelligence (GenAI) techniques to query data for intelligent insights and automated decision-making processes, unlocking hidden value from data.
Leading tasks from exploration to proof of concept (POC) and ensuring smooth transitions to scalable production environments.
Collaborating with data engineers and product managers to ensure the delivery of high-quality production results.
Creating and owning key metrics while developing new models and capabilities for innovative product solutions.
Optimizing scalability and ensuring the performance of data pipelines and ML models, handling large-scale, dynamic datasets.

As a Principal Data Scientist, you will apply your expertise in data analysis, machine learning, LLM agents, and cybersecurity to build new defense techniques against cyber-villains. You will be a driving force in designing and developing groundbreaking, Agentix LLM-based security solutions that block attacks even before they begin.
Your Impact
Contribute to a diverse and highly skilled research group that pioneers state-of-the-art technologies to protect our customers.
Utilize analytical rigor, statistical methods, programming, and data modeling to analyze vast amounts of data, applying your cybersecurity knowledge to guide our focus and approach.
Design and implement agentic LLM solutions to face modern cybersecurity challenges.
Decompose complex problems scientifically and provide actionable insights and recommendations to both technical and non-technical stakeholders.
Lead and collaborate on end-to-end projects within the team and across engineering and product teams, from initial ideation to final deployment.

we are looking for a Data Researcher.
As a Data Researcher, you will be responsible for the core asset of the company - ensuring the ongoing accuracy and superior performance of what is widely recognized as the industry's leading e-commerce fraud decisioning system.
You will be empowered and expected to constantly innovate, devising smart logical and technical solutions to address real and evolving business challenges faced by the world's largest and most sophisticated online retailers, who constitute our primary clientele.
In this capacity, your work will also include some direct engagement with these key customers, providing analytical insights and helping to tailor solutions to their specific needs.
You will join a dynamic department with a deeply ingrained culture of striving for excellence and being the best in our field.
We foster an informal, collaborative environment where your contributions are highly valued.
This role offers significant growth opportunities, with clear pathways for advancement in both managerial and senior individual contributor (IC) capacities, allowing you to shape your career based on your strengths and aspirations. Your work will directly influence our product, protect our customers, and help define the future of trust in digital commerce.
What you'll be doing:
Invent, design, implement, and refine our systems core decisioning logic and models in a live production environment.
Conduct in-depth research into complex fraud patterns, adversarial networks, and emerging global threats.
Leverage rich datasets to derive actionable insights, develop new system components, and advance our feature engineering processes.
Develop, prototype, and automate new tools and processes to enhance the precision and scale of our systems.
Collaborate with a world-class team of Data Scientists, Analysts, Researchers, and Engineers to develop the next generation of AI technology.

As a data scientist you will work directly with engineers, sales, product and clients in order to translate business requirements to production level prediction models and algorithms.

What Youll do

Research and find creative solutions to a unique set of problems
Develop and maintain machine learning models and optimization algorithms from research to production
Develop data infrastructure and pipelines
Collaborate with engineers, sales, product and clients

Were looking for a Data Scientist to join our Data Labs department, which specializes in professional services for our super premium customers.
This role will report to our Datalabs Team Manager in the, R&D.
Why is this role so important?
We are a data-focused company, and our unique AI and machine learning capabilities are the center of our business.
As part of this role, you will create data models that help analyze the petabytes of data we receive from various sources, and research and develop new features and capabilities for our product solutions
As a data scientist in the Datalabs team, you will work on the very core of the company. Part of your role will be to turn raw data into usable metrics and develop new models and statistical algorithms to support out-of-the box requests from customers who want custom digital insights. The Datalabs departments customer centric and business-oriented nature also means you will be supporting a team of data analysts and consultants who interact directly with customers. Together with them, you will translate the voice of these customers into best-in-class digital insights.
So, what will you be doing all day?
Your role as part of the R&D department, and as part of the Datalabs team means your daily responsibilities may include:
Working on versatile use cases within a dynamic, fast paced production environment
Strategic thinking and problem solving, with a strong business sense
Analyzing data from various sources, and turning it into usable input
Understanding various use cases from different customers, and creating models that can translate these cases into meaningful insights
Initiating newly defined tasks from exploration to proof of concept
Owning the finalization of defined tasks (from POC to deployment in production)
Collaborating with data engineers to make sure we reach the desired production results
Owning the ongoing validation process for existing metrics
Collaborating and brainstorming best practices with other teams within the R&D department
Deploying machine-learning models into production for an ongoing use.