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LeadГибридПолная занятость

Data Science Researcher

Оценка ИИ

Отличная позиция в компании-лидере рынка с фокусом на самые передовые технологии (LLM, Multi-agent systems). Гибридный график работы и масштабные задачи делают вакансию крайне привлекательной для топовых специалистов.


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Сложность вакансии

ЛегкоСложно
Оценка ИИ

Роль требует глубоких экспертных знаний в области LLM и агентных систем (Agentic AI), а также опыта вывода исследовательских прототипов в продакшн. Высокая сложность обусловлена необходимостью совмещать глубокую техническую работу с лидерскими функциями и менторством.

Анализ зарплаты

Медиана160 000 $
Рынок130 000 $ – 200 000 $
Оценка ИИ

Зарплата для данной позиции уровня Lead в Израиле обычно находится в верхнем сегменте рынка. Учитывая специализацию на дефицитных LLM и Agentic AI, компенсация может превышать средние значения для стандартных Data Science ролей.

Сопроводительное письмо

I am writing to express my strong interest in the Lead Data Science Researcher position at NICE. With a robust background in architecting production-grade AI agents and a deep expertise in LLM orchestration, I am drawn to NICE’s commitment to challenging the limits of enterprise CX through breakthrough AI research. My experience aligns perfectly with your need for a technical authority who can bridge the gap between experimental agentic systems and reliable, real-world deployments.

In my previous roles, I have successfully led end-to-end research initiatives, focusing on multi-agent systems and complex reasoning tasks using frameworks like LangChain and custom runtimes. I pride myself on maintaining high analytical rigor while ensuring solutions remain 'fit for purpose' and scalable. I am particularly excited about the opportunity to mentor a talented team of researchers and contribute to NICE’s long-term agentic-AI roadmap, leveraging my skills in Python, AWS Bedrock, and modern ML libraries to deliver high-impact results.

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Присоединяйтесь к лидерам рынка AI и создавайте будущее агентных систем в NICE — откликайтесь сейчас!

Описание вакансии

At NiCE, we don’t limit our challenges. We challenge our limits. Always. We’re ambitious. We’re game changers. And we play to win. We set the highest standards and execute beyond them. And if you’re like us, we can offer you the ultimate career opportunity that will light a fire within you.

So, what’s the role all about?

Join NICE’s Research Group and shape the next generation of AI for enterprise CX. As a Lead Data Science Researcher, you will own highimpact research initiatives across NLP, Vision, and multimodal domains, with a strong emphasis on large language models (LLMs) and agenticAI systems

You will combine deep handson technical work with leadership—setting direction, mentoring peers, and translating breakthrough ideas into reliable, productiongrade capabilities for NICE’s contact center solutions.

You will collaborate closely with researchers, engineers, product leaders, and subjectmatter experts to define strategy, validate research hypotheses, and lead the transition from experimental agentic systems to reliable, realworld deployments.

How will you make an impact?

  • Lead end‑to‑end research initiatives across NLP, Vision, and multimodal modeling, with a strong focus on LLM‑based and agentic‑AI systems.
  • Architect, prototype, and evaluate singleagent and multiagent systems, including planning, tool use, memory, and orchestration.
  • Establish and own best practices for safe, controllable, and scalable AI agents, including evaluation frameworks, guardrails, fallback strategies, and observability.
  • Act as a technical authority on LLM and agentic systems, guiding architectural decisions, evaluation strategies, and engineering tradeoffs.
  • Define rigorous offline and online evaluation strategies (KPIs, A/B testing, cost/performance tradeoffs) grounded in realworld constraints.
  • Deliver select research components at production quality and partner closely with productization teams to harden and deploy endtoend solutions.
  • Mentor researchers and data scientists, raising the bar for technical rigor, engineering quality, and applied research impact.
  • Communicate complex findings and risks clearly to crossfunctional stakeholders and leadership.
  • Stay at the forefront of AI research, contributing to the team’s agentic‑AI roadmap and long‑term research vision and help set teamwide standards and guidelines.

Have you got what it takes?

  • Skills-first profile with proven, hands‑on impact in applied AI. (Formal degrees welcome but not required.)
  • Strong Demonstrated experience building production‑grade AI agents that perform multi‑step reasoning and tool‑based actions (e.g., tool invocation, planning, memory).
  • Mandatory: Experience with agent frameworks/orchestration layers or custom agent runtimes (e.g., LangGraph/LangChain, semantic routers, workflow engines, or in‑house frameworks).
  • Strong practical expertise with LLMs (AWS Bedrock or similar platforms), including evaluation, prompt/program design, and safety patterns.
  • Strategic problem-solving leadership: You proactively shape ambiguous business questions into well-defined  analytical goals, challenge underlying assumptions, and ensure the work is focused on the problems with the highest impact.
  • Barsetting analytical rigor—applied pragmatically:You anticipate bias, confounders, and risks of misinterpretation early, apply the right level of methodological rigor for the decision at hand, and help others distinguish between “theoretically perfect” and “fit for purpose.”
  • Efficient, scalable thinking:You balance depth with speed, favor simple and robust solutions over unnecessary complexity, turn one‑off analyses into reusable insights, and help the organization avoid reinventing or over‑engineering solutions.
  • Track record of translating research into reliable systems in partnership with engineering/product teams.
  • Proficiency in Python and modern ML/DL libraries; strong AI engineering skills (clean architecture, testing, CI/CD, observability), as well as familiarity with HuggingFace or similar model ecosystems and open‑source tooling.
  • Experience applying GenAI to DS workflows (LLM‑as‑a‑judge, synthetic data generation, weak labeling, automated eval).
  • Excellent communication and mentoring skills; fluency in English.

You will have an advantage if you also have:

  • Experience with multi‑agent systems, reinforcement learning, or policy optimization for agent control.
  • Expertise in multimodal or vision‑based deep learning.
  • Operating experience with cloud ML at scale (AWS or equivalent).
  • Leading/mentoring globally distributed teams.

What’s in it for you?

Join an ever-growing, market-disrupting, global company where the teams – comprised of the best of the best – work in a fast-paced, collaborative, and creative environment! As the market leader, every day at NiCE is a chance to learn and grow, and there are endless internal career opportunities across multiple roles, disciplines, domains, and locations. If you are passionate, innovative, and excited to constantly raise the bar, you may just be our next NiCEr!

Enjoy NiCE-FLEX!

At NiCE, we work according to the NiCE-FLEX hybrid model, which enables maximum flexibility: 2 days working from the office and 3 days of remote work, each week. Naturally, office days focus on face-to-face meetings, where teamwork and collaborative thinking generate innovation, new ideas, and a vibrant, interactive atmosphere.

#LI-Hybrid

Requisition ID: 10398

Reporting into: Group Lead, Data Science, CX

Role Type: Individual Contributor

*About NiCE*

NICE Ltd. (NASDAQ: NICE) software products are used by 25,000+ global businesses, including 85 of the Fortune 100 corporations, to deliver extraordinary customer experiences, fight financial crime and ensure public safety. Every day, NiCE software manages more than 120 million customer interactions and monitors 3+ billion financial transactions.

Known as an innovation powerhouse that excels in AI, cloud and digital, NiCE is consistently recognized as the market leader in its domains, with over 8,500 employees across 30+ countries.

NiCE is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, age, sex, marital status, ancestry, neurotype, physical or mental disability, veteran status, gender identity, sexual orientation or any other category protected by law.

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Создайте идеальное резюме с помощью ИИ-агента

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Навыки

  • Python
  • Large Language Models
  • Generative AI
  • LangChain
  • NLP
  • Computer Vision
  • AWS Bedrock
  • Hugging Face
  • CI/CD
  • Reinforcement Learning
  • PyTorch
  • TensorFlow

Возможные вопросы на собеседовании

Проверка практического опыта работы с современными фреймворками для создания агентов.

Расскажите о самом сложном AI-агенте, которого вы спроектировали: как вы реализовали планирование, использование инструментов (tool use) и управление памятью?

Оценка способности кандидата обеспечивать надежность систем в условиях неопределенности LLM.

Какие стратегии и guardrails вы используете для обеспечения безопасности и предсказуемости поведения агентов в реальных бизнес-сценариях?

Проверка навыков оценки качества моделей, что критично для Data Science.

Как вы выстраиваете процесс оценки (evaluation) для агентных систем, где результат не всегда бинарен? Какие метрики вы считаете ключевыми?

Оценка лидерских качеств и умения работать с бизнесом.

Опишите случай, когда вам пришлось переводить абстрактную бизнес-задачу в конкретную исследовательскую гипотезу. Как вы определяли приоритеты?

Проверка инженерной культуры.

Как вы обеспечиваете переход от экспериментального кода в Jupyter Notebook к надежному, поддерживаемому коду в продакшн-среде?

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