The role

Nebius is looking for a Senior Data Scientist to build and deploy time series forecasting and classical machine learning models that support core business planning and operational decisions. You will own problems end-to-end, from data exploration and feature engineering to model deployment and monitoring, working with large-scale, real-world datasets.

The role emphasizes strong statistical thinking, robust modeling, and production reliability over experimentation with trendy frameworks. Your work will directly impact forecasting accuracy, resource planning, and key business metrics.

You’re welcome to work in our offices in Tel Aviv.

Your responsibilities will include: 

• Time series forecasting. Design, build, and maintain forecasting models (e.g., demand, usage, capacity). Evaluate performance using appropriate metrics and improve accuracy over time.
• Classical ML modeling. Develop and deploy models using regression,Binary classifcatiom ,  tree-based methods, and other well-established approaches where they provide the best trade-off between performance, interpretability, and maintainability.
• Feature engineering & data preparation. Build robust pipelines for data cleaning, transformation, and feature generation (including time-based features, seasonality, and external signals).
• Model evaluation & monitoring.Define evaluation frameworks, backtesting strategies, and monitoring to ensure models remain stable and reliable in production.
• Production & MLOps. Deploy models into production environments, collaborate on pipeline orchestration, and ensure reproducibility and version control.
• Exploratory analysis. Analyze large datasets to identify patterns, anomalies, and drivers of change in time-dependent behavior.
• Stakeholder collaboration. Work closely with business and product teams to define forecasting needs, align on success metrics, and translate model outputs into actionable insights.
• Cross-domain contribution. Contribute to adjacent data science areas (e.g., LLM-based systems) as needed, ensuring shared ownership and continuity across team responsibilities.

We expect you to have: 

• Experience as a data scientist working in production environments (5+ years).
• Experience with time series modeling and forecasting techniques.
• Experience building reliable data pipelines and working with large datasets.
• Experience with modern data science tools and ecosystems using Python (e.g., NumPy, Pandas, Scikit-learn, deep learning frameworks).
• Strong SQL skills and experience working with large datasets.
• Strong foundation in statistics and machine learning fundamentals.
• Background in Computer Science, Statistics, Mathematics, Industrial Engineering, Economics, or a related field (Master’s degree or equivalent).
• Demonstrated ability to take models from idea to production and ensure ongoing value.
• Demonstrated ability to apply structured thinking and robust evaluation in forecasting problems.
• Strong communication skills and ability to explain model outputs, uncertainty, and limitations.
• Working knowledge of spoken and written English.

It will be an added bonus if you have: 

• Experience working in cloud environments (preferably Azure).
• Experience with MLOps tools and production model lifecycle management.
• Experience with workflow orchestration tools such as Apache Airflow.
• Familiarity with LLM-based systems (e.g., evaluation, RAG pipelines) in applied settings.

SUMMARY

We're looking for a AI Research Scientist to join us in spreading the power of Wiz and push the boundaries of AI in cybersecurity. You'll be at the forefront of developing novel AI models - focusing transformers and LLMs - that advance how cybersecurity operates. Contribute to the wider AI and cyber communities through publications and conference presentations, establishing Wiz as a thought leader at the intersection of AI and cybersecurity.

WHAT YOU’LL DO

• Develop and research novel AI models, focusing on transformers and deep learning. Lead mid- to long-term projects aimed at advancing AI-driven features in the cybersecurity domain for Wiz products.
• Conduct experiments and evaluate the performance of AI models, algorithms, and techniques using real-world datasets and simulated environments.
• Stay informed about cutting-edge AI methodologies, frameworks, and tools and apply them to improve security solutions’ accuracy, efficiency, and scalability.
• Collaborate with engineering teams to design, build, and maintain production pipelines. Work closely with the Security Research and Product teams to define research goals.
• Publish research findings and AI thought leadership content and present at leading conferences such as NeurIPS, ICML, or CVPR.

WHAT YOU’LL BRING

• An M.Sc. degree in computer science, statistics, or a related field is a must; a Ph.D. degree is an advantage.
• At least 3 peer-reviewed publications in reputable academic journals or conferences.
• 5+ years of experience in leading and managing data science and machine learning projects, preferably at the intersection of AI and cybersecurity.
• Experience and hands-on familiarity with distributed cloud systems.  
• Strong knowledge of deep learning models and common model architectures such as transformer models, LLMs, CNNs, RNNs. Knowledge of programming languages that are used in AI research—like Python—and experience with AI frameworks (e.g., Hugging Face, LangChain, OpenAI, scikit-learn, TensorFlow, PyTorch).
• Proven ability to work independently in a fast-paced environment and come up with creative solutions to challenging problems.
• Excellent communication (both written and verbal) and presentation skills.

ADVANTAGE

• Knowledge of cybersecurity principles, attack vectors, and defense mechanisms.
• Experience speaking at data science and AI conferences like NeurIPS, ICML, or CVPR.

SUMMARY

We’re looking for a Data scientist Expert to join us and spread the power of Wiz. As a Data Scientist you will be responsible for driving research and development of autonomous AI agents and LLM-powered systems at Wiz. 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 company’s security posture.

WHAT YOU’LL DO

• Lead applied research on AI agents and LLM-driven features in the Wiz 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

WHAT YOU’LL BRING

• An M.S. or Ph.D. degree in computer science, statistics, or related field OR equivalent work experience
• 5+ years of experience in leading data science and machine learning projects, with significant hands-on work building LLM-based applications or AI agents
• Deep practical experience with LLMs - prompt engineering, fine-tuning, model selection, and understanding trade-offs across providers and model families
• Experience with distributed cloud systems - hands-on familiarity with cloud-native architectures at scale
• Strong knowledge of deep learning models and common model architecture such as transformer models
• Knowledge of programming languages that are used in AI research, such as Python, and experience with AI frameworks (e.g., Hugging Face, LangChain, OpenAI, scikit-learn, TensorFlow, PyTorch)
• Ability to work independently in a fast-paced, and come up with creative solutions to challenging problems
• Excellent communication (both written and verbal) and presentation skills
• Advantage: Knowledge of cybersecurity principles, attack vectors, and defense mechanisms

Who we are

DV is the leader in digital performance solutions, helping our advertiser and agency partners verify the quality of their digital campaigns, Optimise to improve performance and Prove that they’re achieving their business outcomes, through unbiased 3rd party data and analytics. DV’s mission is to be the definitive source of transparency and data-driven insights into the quality and effectiveness of digital advertising for the world’s largest brands, agencies, publishers, and digital ad platforms.  Since 2008, DV has helped hundreds of Fortune 500 companies gain the most from their media spend by delivering best-in-class solutions across the digital advertising ecosystem, helping to build a better industry. Learn more at www.doubleverify.com.

What you will do

You will lead a team of experienced Data Scientists while remaining deeply involved in the technical work.

This is a hands-on leadership role (~70% hands-on) combining direct modeling work with ownership of team direction and execution.

You will work on core systems that operate at a massive scale, where:

• Data is abundant, but labels are scarce and expensive

• problems are long-tail and ambiguous

• Systems must meet strict latency and cost constraints (pre-bid)

Your responsibilities include:

• Lead development of content classification systems across social platforms (Meta, TikTok, YouTube), web, and apps

• Design and build models across computer vision, NLP, and multimodal pipelines

• Own the full lifecycle: data selection -> labeling strategy -> training -> evaluation -> deployment

• Develop strategies for efficient data curation and labeling (active learning, auto-labeling, sampling under scale)

• Improve model quality (precision/recall) while balancing cost, latency, and scale

• Drive automation systems (auto-labeling, auto-curation, retraining loops)

• Apply modern AI approaches (LLMs, embeddings, foundation models) to real production problems

• Lead and mentor a team of senior Data Scientists, setting technical direction and pushing execution forward

• Work closely with ML Engineering, Product, and Policy to translate ambiguous requirements into scalable systems

Who you are

• 3+ years of experience leading Data Science / ML teams

• 6+ years of hands-on experience in Machine Learning / Deep Learning

• Strong background in Computer Vision and/or NLP

• Experience building and deploying production ML systems at scale

• Strong understanding of real-world trade-offs (accuracy, cost, latency)

Technical requirements

• Hands-on experience with deep learning frameworks (PyTorch / TensorFlow)

• Experience with ML/DS tools (scikit-learn, OpenCV, HuggingFace, etc.)

• Experience working with large datasets and model evaluation pipelines

Advantages

• Experience with multimodal systems (vision + text + audio)

• Experience with LLMs / embeddings / foundation models

• Experience with AutoML, active learning, or data-centric AI

#Hybrid#
 

About Pagaya

Pagaya is a global technology company making life-changing financial products and services available to more people nationwide, as it reshapes the financial services ecosystem. By using machine learning, a vast data network and a sophisticated AI-driven approach, Pagaya provides comprehensive consumer credit and residential real estate solutions for its partners, their customers, and investors. Its proprietary API and capital solutions integrate into its network of partners to deliver seamless user experiences and greater access to the mainstream economy. Pagaya has offices in New York and Tel Aviv. For more information, visit pagaya.com.

About the Role

Pagaya is 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 Pagaya 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

Required Qualifications:

• 3+ years of experience in Data Science roles with experience with ML models- Must
• Work experience in a financial company
• Python - experience with data science packages (pandas, numpy,  sklearn, seaborn)
• Bachelor's degree in Data Science, Statistics, Computer Science, or a related quantitative field
• Excellent problem-solving skills with the ability to think critically and creatively
• Strong communication skills and the ability to work effectively in a collaborative team environment
• Fluent in English, both verbal and written

Preferred Qualifications:

• Masters degree
• Experience in Finance, specifically with financial data or models - advantage
• Experience with cloud platforms (e.g., AWS) and distributed computing
• Familiarity with regulatory compliance requirements for financial models (e.g., SR 11-7)

Our Team

Pagaya was founded in 2016 by seasoned research, finance, and technology entrepreneurs, and we are now 500+ strong in New York, Los Angeles, and Tel Aviv.

We move fast and smart, identifying new opportunities and building end-to-end solutions from AI models and unique data sources. Every Pagaya team member is solving new and exciting challenges every day in a culture based on partnership, collaboration, and community.

Join a team of builders who are working every day to enable better outcomes for our partners and their customers.

Our Values

Our values are at the heart of everything we do. We believe great solutions are built through a great community.

• Advance Inclusion- We create a world where everyone can win, designing systems that better represent people and generate sustainable value for our employees, partners and investors.
• Be Accountable Together- We proudly own our actions and our results, taking initiative to ensure our work gets over the finish line as a team.
• Continuously Learn- We challenge ourselves for the sake of getting better as individuals, as teams, and as an organization to deliver for our partners.
• Debate and Commit- We respectfully and openly debate to strengthen our ideas and build shared conviction - once we decide, we go all in, together.
• Dream Big and Act- We boldly tackle complex problems, pressure-test solutions in real-time, and adapt with speed and energy.

More than just a job

We believe health, happiness, and productivity go hand-in-hand. That's why we're continually looking to enhance the ways we support you with benefits programs and perks that allow every Pagayan to do the best work of their life. 

Pagaya is an equal opportunity employer. Pagaya is encouraging diversity and actively seeking applicants from all backgrounds, as are committed to creating a diverse workforce together with an inclusive environment for all. Employment is decided on the basis of qualifications, skills, and business needs.

Pagaya is an equal opportunity employer. Pagaya is encouraging diversity and actively seeking applicants from all backgrounds, as are committed to creating a diverse workforce together with an inclusive environment for all. Employment is decided on the basis of qualifications, skills, and business needs.

The opportunity
Join a high-impact ML team building state-of-the-art systems that optimize experiences for billions of users. You'll tackle challenging problems across diverse datasets - with the freedom to explore novel approaches and infrastructure to deploy them at scale.

What Success Looks Like:

Short-term: Ship your first production model with measurable impact within 3 months.

Long-term: Own major ML initiatives end-to-end and introduce new methodologies that expand the team's capabilities.

Your Impact:

Elevate our technical bar with fresh ML perspectives. Shape our roadmap by identifying opportunities others miss. Your research skills keep us cutting-edge while your execution speed drives results.

What You'll Gain:

Work on real-time ML systems at scale with rich, diverse data

Autonomy to define problems and drive projects from idea to impact

Freedom to explore emerging techniques and expand your scope

Fast feedback loops through strong experimentation infrastructure

What you'll be doing

• Join a high-impact ML team building state-of-the-art systems that optimize experiences for billions of users. You'll tackle challenging problems across diverse datasets - with the freedom to explore novel approaches and infrastructure to deploy them at scale.
• What Success Looks Like:
• Short-term: Ship your first production model with measurable impact within 3 months.
• Long-term: Own major ML initiatives end-to-end and introduce new methodologies that expand the team's capabilities.
• Your Impact:
• Elevate our technical bar with fresh ML perspectives. Shape our roadmap by identifying opportunities others miss. Your research skills keep us cutting-edge while your execution speed drives results.
• What You'll Gain:
• Work on real-time ML systems at scale with rich, diverse data
• Autonomy to define problems and drive projects from idea to impact
• Freedom to explore emerging techniques and expand your scope
• Fast feedback loops through strong experimentation infrastructure

What we're looking for

• Strong Deep Learning Expertise – Comprehensive knowledge of DL theory paired with the practical intuition gained from training many networks; comfortable working with SOTA pretrained models while understanding the underlying mechanics of convergence and scale.
• Proven ability to deliver production ML models with measurable business impact - from problem definition through A/B testing -> deployment and outcome tracking
• AI-Native Builder Mentality – Comfortable breaking conventional development cycles to build fast and ship often. You have a deep mastery of the modern GenAI stack for development, using it to automate the mundane and focus your cognitive load on high-level architecture and model performance.
• Strong programming skills in Python and Deep Learning stack (PyTorch, scikit-learn, XGBoost) with ability to write clean, efficient code for production systems
• Self-directed research capability - demonstrated ability to independently explore unfamiliar ML domains, synthesize technical literature, and implement novel approaches
• Structured problem-solving methodology - ability to decompose complex business problems, design solution approaches, and communicate technical findings to stakeholders

You might also have

• Positivity and enthusiasm

Additional information

• Relocation support is not available for this position
• Work visa/immigration sponsorship is not available for this position

Benefits
At Unity, we want our team members to thrive. We offer a wide range of benefits designed to support well-being and work-life balance.

Please note: Benefits eligibility, specific offerings, and coverage vary based on the country and employment status.

While specific benefits vary, here are some of the ways we strive to take care of our eligible team members globally: Comprehensive health, life, and disability insurance | Commute subsidy | Employee stock ownership | Competitive retirement/pension plans | Generous vacation and personal days | Support for new parents through leave and family-care programs | Office food snacks | Mental Health and Wellbeing programs and support | Employee Resource Groups | Global Employee Assistance Program | Training and development programs | Volunteering and donation matching program

Life at Unity
Unity [NYSE: U] is the world’s leading game engine, powering play for more than 3 billion consumers each month. The top mobile games in the world, the most played PC indie titles, the most innovative console games, and virtually all of the top XR and Web Games are developed, deployed, and grown in Unity. Unity also enables teams across industries like automotive, manufacturing, and healthcare to design, simulate, and collaborate in 3D — closing the gap between ideas and reality. For more information, please visit www.unity.com.

Unity is a proud equal opportunity employer. We are committed to fostering an inclusive, innovative environment and celebrate our employees across age, race, color, ancestry, national origin, religion, disability, sex, gender identity or expression, sexual orientation, or any other protected status in accordance with applicable law. Our differences are strengths that enable us to support the growing and evolving needs of our customers, partners, and collaborators. If you have a disability that means there are preparations or accommodations we can make to help ensure you have a comfortable and positive interview experience, please fill out this form to let us know.

This position requires the incumbent to have a sufficient knowledge of English to have professional verbal and written exchanges in this language since the performance of the duties related to this position requires frequent and regular communication with colleagues and partners located worldwide and whose common language is English.

Headhunters and recruitment agencies may not submit resumes/CVs through this website or directly to managers. Unity does not accept unsolicited headhunter and agency resumes. Unity will not pay fees to any third-party agency or company that does not have a signed agreement with Unity.

Your privacy is important to us. Please take a moment to review our Prospect Privacy Policy and Applicant Privacy Policy. Should you have any concerns about your privacy, please contact us at DPO@unity.com.

#SEN

The Data Science role at Armis is the engine behind our industry-leading Exposure Management (EM) platform.
You will be responsible for the AI models that power our CAASM (Cyber Asset Attack Surface Management) capabilities and our advanced Vulnerability Prioritization and Remediation engines.

We are building the intelligence layer that helps organizations implement a Continuous Threat Exposure Management (CTEM) framework. You will build models that normalize fragmented data from hundreds of sources, calculate complex risk scores, and prioritize which exposures actually pose a threat to the business.

We are looking for an experienced and creative data scientist, with a software development touch, to join our Data Science and Armis family. A data scientist that understands and loves data, and lots of it.

 What you will do...

• Solve Applied Product Challenges: Deep-dive into the Armis product ecosystem to identify and solve high-impact problems. You will translate complex customer needs into scalable ML features that directly improve the user experience.
• Lead Exposure Intelligence R&D: Develop features that unify asset data (CAASM) with threat intelligence. This includes building models for entity resolution (deduplicating assets across fragmented sources) and automated risk assessment.
• Advanced NLP & Knowledge Extraction: Use NLP and LLMs to parse unstructured security data—such as CVEs, threat intel feeds, and security advisories—to automate the mapping of vulnerabilities to specific business contexts.
• Predictive Prioritization: Design and optimize algorithms that go beyond static CVSS scores. You will incorporate exploitability (EPSS), reachability, and business criticality to help clients focus on the 1% of exposures that matter most.
• End-to-End Ownership: Work closely with Product Managers and Data analysts and Engineers to ensure your models aren't just accurate in a notebook, but are robust, explainable, and deliver clear value within the product UI.
• Graph-Based Attack Surface Mapping: Identify hidden patterns and relationships between assets, users, and vulnerabilities to visualize the potential "blast radius" of a security gap.

 What we expect...

• Academic Background: M.Sc./PhD in Computer Science, Statistics, Engineering, or a related field (or equivalent high-level professional experience).
• Industry Experience: 6+ years in Data Science, with a heavy focus on NLP and solving complex, real-world problems using ML/Deep Learning.
• Technical Mastery: Hands-on experience with PyTorch, Hugging Face, scikit-learn, and SQL. Familiarity with processing large-scale datasets (PySpark, or similar) is highly valued.
• Domain Awareness: Proven ability to apply statistical modeling to cybersecurity, risk management, or complex system analysis. Experience with Vulnerability Management or Graph Theory is a significant plus.
• Product and collaborative Driven Mindset: You are obsessed with understanding the "Why" behind the data. You enjoy learning the nuances of the product and the cybersecurity domain to ensure your DS solutions are highly applicable.

Curiosity & Grit: A passion for diving into "messy" data and finding the signal within the noise of the modern attack surface.