דרושים » תוכנה » Senior Data Scientist

Requirements:
Proven strong expertise (8+ years) as a data scientist and machine-learning researcher.
Proven strong expertise (8+ years) in Python, with a production-level design and coding skills and hands-on experience with coding machine learning / statistical modeling based solutions
M.Sc. in Computer Science, Mathematics, Engineering or a related field, with strong theoretical background in supervised & unsupervised modeling and various other statistical modeling techniques
High-level experience with databases approaches, such as SQL and document-oriented (e.g. MongoDB) and big data
Experience in data analysis and visualization
Strong problem solving and critical thinking skills
Can-do approach
Background in Cybersecurity - an advantage
Theoretical and practical background in Generative AI - an advantage

Requirements:
What Experience Will Drive to Success:
* Bachelors degree in data Science, Computer Science, Computer Engineering, or related field.
* 2+ years of experience in AI/ML engineering, with a proven track record of building and deploying ML & AI systems.
* Strong programming skills in Python and experience with ML frameworks such as TensorFlow, PyTorch, and Scikit-Learn.
* Hands-on experience with Big Data processing frameworks (Apache Spark, Dask, Ray).
* Hands-on experience with LLMs and AI Frameworks (LangChain, OpenAI, HuggingFace, LangGraph, etc.)
* Experience with Git and Jenkins.
* Strong problem-solving skills, a passion for innovation, and a self-driven mindset.
* Excellent communication and collaboration skills.
* Familiarity with AWS AI/ML services and cloud-based deployments (Advantage).
* Experience working with MLOps tools, including model registry, experiment tracking, and model serving (Advantage).
What We Are Looking For Independent and Self-Driven: Were building an AI Department from the ground up, so we need someone who is proactive, takes ownership, and thrives in a startup-like environment. Passion for Innovation: Whether its building scalable data infrastructure or creating advanced AI models, we are looking for someone passionate about solving complex challenges and delivering innovative solutions. Collaboration Skills: Appdome is all about teamwork. You will collaborate with engineers, data scientists, and product teams to build impactful solutions. Strong communication and interpersonal skills are key. Adaptability and Problem-Solving: Things move quickly at Appdome. You should be able to adapt to changing requirements and quickly solve problems in a fast-paced, dynamic environment. Can-Do Attitude: Were looking for motivated individuals who take the initiative, face challenges head-on, and can work independently while contributing to team success. About the Company: Appdome's mission is to protect every mobile app worldwide and its users. We provide mobile brands with the only patented, centralized, data -driven Mobile Cyber Defense Automation platform. Our platform delivers rapid no-code, no-SDK mobile app security, anti-fraud, anti-malware, anti-cheat, anti-bot implementations, configuration as code ease, Threat-Events threat-aware UI / UX control, ThreatScope Mobile XDR, and Certified Secure DevSecOps Certification in one integrated system. With Appdome, mobile Developers, cyber and fraud teams can accelerate delivery, guarantee compliance, and leverage automation to build, TEST, release, and monitor the full range of cyber, anti-fraud, and other defenses needed in mobile apps from within mobile DevOps and CI/CD pipelines.

Requirements:
Natural scientific curiosity and ability to handle complex problems
At least 6 years of experience in hands-on data science projects
High proficiency in python and at least good familiarity with SQL
Advanced degree (MSc or PhD) in Machine Learning, Computer Science, Electrical Engineering, Physics, Statistics, Applied Mathematics, or a related field or equivalent military experience required
Deep understanding of probability, statistics, and machine learning models with a proven track record of selecting, modifying, and applying advanced algorithms to solve practical problems
Demonstrated ability to run end-to-end research POCs, from conceptualization to solutions, including designing, executing, analyzing, and concluding research methodologies and outcomes
Good communication skills, with the ability to convey complex research findings clearly and effectively to both technical and business audiences
Preferred
Background in the cybersecurity domain
Experience with recommender systems
Experience working with big data platforms (e.g., GCP)
Experience with LLM-based algorithm design
Familiarity with cloud-native architectures and services for data processing.

Requirements:
Were looking for someone whos not just a great engineer, but a passionate innovator who puts their soul into solving tough problems and delivering value.
* 4-5+ years of experience in researching, developing and delivering ML solutions in production-scale environments.
* Solid foundation knowledge of data science, Machine Learning, and statistics.
* Demonstrated analytical thinking and a deep understanding of data - its structure, context, and the insights it can unlock.
* Strong Python programming skills with fluency in AI/ML frameworks: Scikit-learn, TensorFlow, PyTorch, Hugging Face, LangChain, etc.
* Expertise in working with large-scale datasets using SQL, Spark, or similar tools.
* Proven success translating product or business needs into working AI systems.
* Fast learner, creative, and comfortable working in a dynamic startup environment.
* Good communication skills, able to explain complex ideas and findings to both technical and business audiences. Bonus Points (Preferred)
* Experience with cybersecurity-related data or product domains.
* Hands-on knowledge in working with LLMs and building AI agents.
* Familiarity with AWS cloud environment and MLOps (ML Orchestration, Docker, Kubernetes, MLflow, etc.). This position is also open to Security Researchers with data and AI experience who are looking to expand in AI. Ready to Empower the Future? At Cynet, you wont just be another data Scientist. Youll be a thought leader. A builder. An innovator. This is a unique opportunity to envision and shape how AI defends tomorrows digital landscape. If you're ready to dive deep, move fast, and create meaningful impact - wed love to meet you Apply now and lets build the future of cybersecurity together.

Requirements:
5+ Years as a Data Scientist with a proven production experience
Experience in conducting applied research
Collaborative teammate with great communication skills
Strong programming skills in Python
Strong problem solving skills
Curiosity and the passion to learn about new technologies and challenges
Advantageous: Familiarity with modern software engineering practices and tools
Advantageous: cyber security background

Requirements:
Requirements
BSc in Computer Science, Engineering, Mathematics, Physics, or a related quantitative field. MSc is an advantage.
3+ years of hands-on experience in NLP roles with demonstrated production deployment of ML models.
At least 1 year of experience with LLMs (e.g., OpenAI, HuggingFace, Cohere, Anthropic, or similar).
Strong programming skills in Python with practical use of ML and NLP frameworks (e.g., HuggingFace Transformers, spaCy, scikit-learn).
Familiarity with prompt engineering principles, including prompt tuning, template construction, and response evaluation.
Experience with model monitoring and optimization in real-world settings.
Understanding of model limitations, prompt sensitivity, and output consistency.

Advantages:
Knowledge of ML-Ops practices and model deployment pipelines.
Experience with LLM safety, bias mitigation, or prompt hardening strategies.
Exposure to multilingual or multimodal prompting.
Familiarity with compliance frameworks in healthcare or other regulated environments (e.g., HIPAA, SOC2).

Requirements:
5+ years of experience as a Data Scientist, working on machine learning-related projects or equivalent experience
Hands-on experience in modern AI techniques, including LLMs, embeddings, knowledge graphs, retrieval-augmented generation (RAG), multi-agent systems and prompt-engineering
Strong proficiency in Python and relevant ML/AI frameworks (e.g., Hugging Face Transformers, PyTorch, scikit-learn), as well as graph and vector database technologies
Experience working with large datasets and data processing libraries (e.g., Pandas, NumPy, Spark)
Pragmatic approach, open-minded, good communicator who can simplify complex ideas and designs
BSc in Computer Science or related field. MSc - advantage
Background in cybersecurity - advantage.

Requirements:
Minimum of 5 years of experience as a Back End developer.
Deep knowledge of Generative AI principles, including Large Language Models (LLMs) and RAG techniques and, modern deployment architectures.
Ability to lead team to design services, modules, APIs, and folder structures that enable REST API communication and facilitate a plug-and-play approach for various agent pods (compatible with langgraph, pydanticAI, etc.)
Practical Implementation: Hands-on experience in implementing and integrating new ideas and tools within the GenAI landscape.
Programming and Tools: Proficiency with Python, PySpark, Langchain, LlamaIndex, RAG, ChromaDB, QDrant, Weaviate, Neo4j, Knowledge Graphs, AWS Bedrock, GCP Vertex, Azure OpenAI, Git/GitHub, Docker, SQL, FastAPI, PyTorch/TensorFlow, and Pydantic.
Cloud Platforms: Experience with managed cloud services provided by hyperscalers such as AWS, Azure, or GCP.
Excellent problem-solving and analytical skills. Degree in Computer Science, Artificial Intelligence, Machine Learning or a related field.
Advanced level of English.
Working Israeli permit- a must
B.A/M.Sc. in Data Science, Computer Science, Mathematics, Statistics, etc- an advantage

Requirements:
5+ years building data‑intensive or distributed production systems with Python and relevant ML ecosystems, shipping production software.
3+ years deploying machine‑learning models (classical and/or LLM) in cloud environments (AWS/GCP/Azure) with containers and Kubernetes.
Hands‑on experience with MLOps toolstooling (e.g., MLflow, Kubeflow, SageMaker, Vertex AI, Feast or equivalent).
Proven track record creating robust data/feature pipelines for ML and instrumenting real‑time monitoring for drift and performance.
Strong software‑engineering fundamentals: version control, automated testing, CI/CD, security, and cost awareness.
Excellent collaboration and communication skills in Hebrew and English; comfortable working closely with cross‑functional partners and mentoring peers.
Mindset of ownership, curiosity, and bias for action in a fast‑moving environment.

Requirements:
5+ years of experience in Data Science. Experience in developing ML / DL / LLM / NLP algorithms.
Bachelors or Masters degree in Data Science, Computer Science, Statistics, or a related field, with a significant focus on machine learning.
High proficiency in Python.
Excellent understanding of machine learning techniques, algorithms, and methodology.
Experience with common data science toolkits, such as Pandas, Scikit-learn, Tensorflow, and more.
High-level applied statistics skills, such as distributions, statistical testing, etc.
Experience in data mining and insight drawing from large data sets.
Data-oriented personality, analytical mind, and problem-solving aptitude.
Experience in Constraint programming or Network science - an advantage.
A team player with a can-do attitude, delivery-oriented.