NICE

LeadDataScienceResearcher

$450–750k ~AI est. Raanana, Israel Remote Friendly
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Lead candidates.

The Brief

“Lead Data Science Researcher at NICE. Skills: AI research, Agentic AI systems, LLM, Multimodal modeling. Lead research initiatives. Architect agent systems”

What You'll Achieve.

Translate ideas into capabilities; Transition systems to deployments; Raise bar for impact

Industry & Context.

Problems you'll solve

Strategic problem-solving; Analytical rigor; Efficient thinking; Scalable thinking

What They're Looking For.

Must Have

Experience building production-grade AI agents, Experience with agent frameworks/orchestration layers, Practical expertise with LLMs, Strategic problem-solving leadership, Analytical rigor, Efficient, scalable thinking, Track record of translating research into reliable systems, Proficiency in Python, Modern ML/DL AI engineering skills, Experience applying GenAI to DS workflows, Excellent communication fluency in English, Mentoring fluency in English

Nice to Have

Experience with multi-agent systems, Reinforcement learning experience, Policy optimization experience, Expertise in multimodal deep learning, Expertise in vision-based deep learning, Operating experience with cloud ML at scale, Leading globally distributed teams, Mentoring globally distributed teams

What You'll Do.

Lead research initiatives

Architect agent systems

Prototype agent systems

Evaluate agent systems

Establish best practices

Guide architectural decisions

Guide evaluation strategies

Guide engineering tradeoffs

Define evaluation strategies

Deliver research components

Mentor data scientists

Raise bar for quality

Contribute to roadmap

Set teamwide standards

Set teamwide guidelines

Perform multi-step reasoning

Perform tool-based actions

Apply GenAI to DS workflows

How You'll Work.

Team & Collaboration

Cross-functional stakeholders; Researchers; Engineers; Product leaders; Subjectmatter experts; Productization teams; Engineering teams; Product teams

Communication Scope

Communicate complex findings; Communicate risks; English fluency

Full Job Description

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 t

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