לוח משרות דרושים Data Scientist

We are seeking a Research Scientist to join its Fundamental AI Research (FAIR) organization, focused on making significant advances in Code Generation and LLMs reasoning with specific focus on reinforcement learning, synthetic data generation and advanced scaffolding/agentic techniques. You will have the opportunity to work with a broad and highly interdisciplinary team of scientists, engineers, and cross-functional partners, and will have access to cutting edge technology, resources, and research facilities.
AI Research Scientist Responsibilities
Lead, collaborate, and execute on research that pushes forward the state of the art in agentic code generation
Work towards long-term ambitious research goals, while identifying intermediate milestones
Directly contribute to experiments, including designing experimental details, implement reusable code, running evaluations, and organizing results
Contribute to publications and open-sourcing efforts
Mentor other team members. Play a significant role in healthy cross-functional collaboration,

Required Data Scientist, Product Analytics
As a Data Scientist, you will shape the future of people-facing and business-facing products we build across our entire family of applications. By applying your technical skills, analytical mindset, and product intuition to one of the richest data sets in the world, you will help define the experiences we build for billions of people and hundreds of millions of businesses around the world. You will collaborate on a wide array of product and business problems with a wide-range of cross-functional partners across Product, Engineering, Research, Data Engineering, Marketing, Sales, Finance and others. You will use data and analysis to identify and solve product development's biggest challenges. You will influence product strategy and investment decisions with data, be focused on impact, and collaborate with other teams. By joining us, you will become part of a world-class analytics community dedicated to skill development and career growth in analytics and beyond.
Product leadership: You will use data to shape product development, quantify new opportunities, identify upcoming challenges, and ensure the products we build bring value to people, businesses, and us. You will help your partner teams prioritize what to build, set goals, and understand their product's ecosystem.
Analytics: You will guide teams using data and insights. You will focus on developing hypotheses and employ a varied toolkit of rigorous analytical approaches, different methodologies, frameworks, and technical approaches to test them.
Communication and influence: You won't simply present data, but tell data-driven stories. You will convince and influence your partners using clear insights and recommendations. You will build credibility through structure and clarity, and be a trusted strategic partner.
Data Scientist, Product Analytics Responsibilities
Work with large and complex data sets to solve a wide array of challenging problems using different analytical and statistical approaches
Identify and measure success of product efforts through goal setting, forecasting, and monitoring of key product metrics to understand trends
Partner with Product, Engineering, and cross-functional teams to inform, influence, support, and execute product strategy and investment decisions
Apply technical expertise with quantitative analysis, experimentation, data mining, and the presentation of data to develop strategies for our products that serve billions of people and hundreds of millions of businesses
Define, understand, and test opportunities and levers to improve the product, and drive roadmaps through your insights and recommendations.

Applied Data Scientist
Tel Aviv, Israel (Hybrid On-site)
Full-Time
We are the trust layer backbone for the Generative AI revolution, building the critical testing infrastructure needed to enable the next generation of AI: Agentic Systems. We provide an end-to-end platform that goes beyond simple metrics to evaluate complex, multi-step LLM workflows. Our technology employs a swarm of specialized evaluation agents to validate complex AI workflows and isolate the root cause of errors. We empower organizations to solve the black box problem, ensuring their agents are reliable, safe, and hallucination-free from the first prototype to high-scale production.
About the Role
As an Applied Data Scientist, you will research, design, and implement complex algorithms that assess and monitor AI systems, including cutting-edge LLM applications. You will work in a high-paced environment where impact is key. You will collaborate closely with our engineering and product teams to push the boundaries of what automated AI evaluation can achieve, ensuring our users get the most reliable and actionable insights possible.

We're in search of an exceptional hands-on Data Scientist who can bridge data infrastructure, fraud analytics, and machine learning to enhance our fraud detection capabilities. This role requires someone who can drive projects from ideation to implementation, leading these efforts while thinking strategically about how we detect and prevent fraud at scale. Our ultimate goal is to equip our clients with resilient safeguards against chargebacks, empowering them to safeguard their revenue and optimize their profitability. Join us on this thrilling mission to redefine the battle against fraud.

Your Arena

Develop and enhance fraud detection models from concept to production, focusing on data normalization, network analysis, and risk scoring.
Take ownership to identify, analyze, and implement solutions for fraud patterns and behavioral anomalies.
Design, build and maintain data science pipelines and fraud intelligence systems to improve detection accuracy.
Collaborate with product, engineering, and risk teams to implement fraud prevention strategies.
Own projects end-to-end - balancing short-term wins with long-term strategy.

We are looking for an experienced Data Scientist who can leverage and develop innovative machine learning, NLP, and generative AI technologies, for solving problems within a wide scope.
As a part of our Data Science group, you will work on highly complicated challenges, from research to production, and help shape our algorithms and AI platform. You will work with Developers, Analysts, Product Managers, and business owners on growth opportunities and new ideas.
You should have a strong background and experience in the machine learning pipeline through business understanding, research, data exploration, feature engineering, model building, performance evaluation, testing, production-level code and deployment, model monitoring, and maintenance.
What am I going to do?
Take leading roles in projects such as search engine ranking, promoted ads in our companys search results, recommendations, users segmentation and personalization, online bidding optimization, text analysis, real-time predictions, live streaming data handling, exploration-exploitation problems, etc.
Work closely with various departments in the company to provide advanced Data Science solutions end to end.
Write and own production models and code.
Independent research and innovation in new content and technological domains.
Lead and advise other team members.
Continuously produce new initiatives and improvement ideas.
Act as a leader of our companys AI platform. Develop models and framework solutions for the group.

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 You'll Do:

Devise, initiate, manage and execute cutting edge exploration and exploitation projects.
Apply your knowledge of Data Science and algorithm development to create data solutions.
Analyze extremely large (petabytes) and diverse datasets to solve complex problems, and then develop algorithmic solutions to do it for you.
Proactively seek growth opportunities aligned with core KPIs.
Partner with other functions in the company, to support decision making.
Instant data gratification guaranteed!.

abra is looking for an experienced Data Sales Manager to lead business growth in Data, Analytics, and AI within Microsoft activity. The role involves driving enterprise sales, managing complex deals, and collaborating with technical teams to deliver innovative solutions. Key Responsibilities:
* Lead end-to-end sales for Data, Analytics, and AI solutions.
* Identify and develop new business opportunities.
* Manage relationships with strategic clients at business and IT levels.
* Drive RFP/RFI processes and prepare complex proposals.
* Collaborate with architects, data experts, pre-sale, and delivery teams.
* Build and manage a robust sales pipeline to achieve targets.
* Negotiate and close deals successfully.

Were looking for a Data Scientist Expert to join us and spread the power. In this role, you will lead the next generation of Data Security Posture Management (DSPM) and Secret Detection. You will build the algorithmic engines that discover and protect the world's most sensitive information in the cloud, driving R&D initiatives to implement AI-driven solutions that tackle emerging threats and enhance our customers' security posture.
WHAT YOULL DO
Lead applied research for AI-driven features in our DSPM and Secret Detection domains
Conduct deep research and classification of sensitive data (PII, secrets) across complex structured and unstructured formats
Own the research lifecycle from raw data exploration and failure analysis to production-grade implementation
Identify and assess data security risks and use cases within cloud environments
Leverage LLMs to automate complex security research and enhance data classification at scale
Partner with Engineering, Security Research, and Product teams to define research goals and maintain production pipelines
Evaluate and optimize AI models and algorithms using real-world datasets to ensure high accuracy and scalability.

As a Senior Data Scientist you will be handed a business problem and will be asked to provide an end to end solution - Unpack and thoroughly understand the business problem, define the strategy to deal with it and develop & deploy your solution along with relevant support.

What you'll be doing
Design and implement end-to-end solutions - from business needs all the way to live deployment
Monitor and own models in production
Model, design, and implement machine learning and data mining algorithms
Perform deep data analysis to evaluate performance and recommend improvements
Help, guide and support our business partners to allow for scale and accuracy while adopting your solutions

‍We are looking for a talented, motivated, and results-driven Data Scientist to join our dynamic team. As a part of our growing data science team, youll play a key role in refining, enhancing, and delivering existing products, while also contributing to the research and innovation of new solutions. This is a fantastic opportunity to impact real-world applications and help shape our product offerings.

Responsibilities
Enhance, maintain, and scale existing ML products, ensuring they meet performance and reliability standards.
Develop robust, efficient, and clean Python-based implementations for machine learning pipelines and products.
Collaborate closely with team members and stakeholders, including product managers, to align technical solutions with business objectives.
Contribute applied research, experimentation, and development efforts that continuously improve and evolve our products.
Stay up-to-date with the latest advancements in machine learning, sharing insights to foster continuous learning and improvement within the team.

This role is designed for a researcher who is "hands-on." We value deep theoretical knowledge, but we require the ability to translate that theory into productive, working code within a limited timeframe.

What youll be doing
Long-Horizon Research: Lead specific, deep-dive research initiatives that require advanced methodology (e.g., novel anomaly detection architectures or LLM-based reasoning for security threats) without the pressure of daily sprint cycles.
LLM Innovation: Design and prototype advanced LLM workflows (RAG, Agents, Fine-tuning) to solve specific security challenges that standard APIs cannot handle.
Academic-to-Industry Bridge: Act as a knowledge hub for the team; bring SOTA academic concepts, recent paper findings, and novel techniques into the teams toolkit.
High-Impact Prototyping: Build functional Proofs of Concept (POCs) that the full-time engineering team can eventually operationalize.

We are seeking a hands-on Applied AI Scientist to join our core R&D team and drive the development of next-generation AI systems for autonomous driving. This role sits at the intersection of applied research and deployment - you will go from reading papers to shipping production systems. You will work directly on our multi-layered autonomy architecture, with a primary focus on real-time predictive models for driving decisions.
A deep technical role for someone who thrives on turning cutting-edge research into real, working systems under hard constraints.
Responsibilities:
Own the research-to-deployment cycle for predictive driving models - from literature review and prototyping through to production integration
Design, implement, and iterate on real-time predictive models, including vision-language models, motion prediction models, and inverse reinforcement learning approaches (e.g., imitation learning, reward recovery)
Collaborate on higher-level reasoning systems, contributing to vision-language-action models that handle complex edge cases and long-horizon planning
Bridge cloud-scale training with edge deployment - work on model compression, quantization, speculative decoding, and efficient inference for embedded automotive platforms
Evaluate and integrate state-of-the-art techniques from the broader AI research community into our autonomy stack
Collaborate closely with internal R&D teams to unblock technical challenges, accelerate delivery, and raise the overall technical bar.

we are seeking an experienced data scientist to join our Model Validation team. The ideal candidate will bring a blend of data science knowledge and analytical skills, understanding in Finance and an understanding of the regulatory landscape of credit lending. As a core team member, you will work closely with model developers to assess model performance, data quality, conceptual soundness, and produce thorough, compliant documentation for regulatory review, ensuring our models meet the highest standards. You will be required to challenge the models, helping deliver high-quality validated models for loan pricing and underwriting.
Key Responsibilities:
Conduct thorough validation of ML models to assess performance, data quality, robustness, conceptual soundness, regulatory requirements and more
Conduct independent tests to assess performance and limitations, and establish model assumptions
Suggest and develop alternative models to challenge and improve existing models
Provide insights into the' strengths and weaknesses of models in terms of Data Science methodology and Finance as well as recommend practical solutions.
Prepare comprehensive validation documentation
Support the ongoing monitoring and improvement of existing predictive models
Stay updated on the latest research in ML credit risk modeling and financial news, ensuring that our practices align with industry standards

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.