לוח משרות דרושים Data Scientist בשרון, לחיפוש זה נמצאו 14 משרות

Requirements:
B.Sc./M.Sc. in Computer Science, Statistics, Applied Mathematics, or related field
5+ years of hands-on experience applying machine learning in production environments
Strong Python skills and experience with ML libraries such as scikit-learn, XGBoost, LightGBM, or CatBoost
Proven experience with feature engineering, model selection, and evaluation in real-world scenarios
Strong statistical understanding and ability to reason under uncertainty
Experience working with messy, high-dimensional, or time-series data
Ability to independently own problems and drive them to production

Requirements:
Proven experience (M.S., Ph.D., or equivalent industry experience) in Computer Science, AI, or a related field.
Strong software engineering skills are non-negotiable; demonstrated excellence in solving complex engineering problems, particularly in Python.
A deep, "under the hood" understanding of modern deep learning, including network architectures, loss functions, optimization, and transformers.
Extensive hands-on experience with PyTorch.
A proven track record of training large-scale deep learning models on large datasets.
Ability to thrive in a fast-paced, high-impact environment where solutions are often unclear and require deep exploration.

Requirements:
BSc or MSc in Computer Science, Data Science, Machine Learning, Statistics, Electrical Engineering, or a related field, or equivalent practical experience.
5+ years of hands-on experience in applied machine learning, data science, search, natural-language processing, analytics engineering, or AI-enabled software systems.
Recent experience evaluating LLM, RAG, search, or agent systems using representative datasets, task-specific metrics, human review, failure analysis, and regression testing.
Strong Python and SQL skills, with experience building maintainable data pipelines, experiment workflows, services, or analytical tools.
Practical experience with several areas such as information retrieval, embeddings, hybrid search, reranking, classification, structured outputs, tool calling, or common LLM failure modes.
Strong statistical judgment, including sampling, leakage prevention, uncertainty, calibration, precision and recall, temporal drift, and controlled comparison of competing approaches.
Ability to work with semi-structured engineering data from issue-tracking systems, source control, code reviews, continuous integration, logs, dashboards, and test systems.
Clear communication skills and the ability to explain results, limitations, and tradeoffs to technical and business stakeholders.

Requirements:
BSc or MSc in Computer Science, Computer Engineering, Electrical Engineering, Data Science, or a related field, or equivalent practical experience.
Typically 7+ years of hands-on experience in production software, ML platform, search, data, or infrastructure engineering, including meaningful recent experience shipping LLM-powered systems; exceptional candidates with equivalent depth are welcome.
Strong Python engineering skills and experience designing maintainable APIs, services, libraries, and data pipelines. Experience with Go, Java, or C/C++ is an advantage.
Strong understanding of transformer-based language models and production inference, including tokenization, context management, batching, KV caching, parallelism, quantization, structured output, tool calling, and common model failure modes.
Demonstrated experience building production RAG or enterprise-search systems using embeddings, vector and/or lexical search, metadata filtering, reranking, source attribution, and systematic retrieval evaluation.
Experience defining task-specific LLM evaluations using representtive datasets, strong baselines, domain-expert review, automated metrics, human feedback, error analysis, and regression thresholds.
Experience deploying and operating containerized services on Linux using Docker and Kubernetes or an equivalent orchestration environment.
Practical experience with GPU-backed model serving, performance profiling, capacity planning, monitoring, and reliability engineering.
Strong knowledge of distributed-system fundamentals, authentication and authorization, API security, secrets handling, encryption, auditability, and data lifecycle controls.
Experience with Git, automated testing, CI/CD, infrastructure as code, observability, and production incident response.
Sound technical judgment about quality, security, maintainability, hardware efficiency, and total cost-not just model benchmark scores.
Ability to lead an ambiguous, cross-functional initiative, explain complex AI behavior in plain language, and help other teams ship safely on a shared platform.

Requirements:
Required Skills and Experience :
A Ph.D. (or equivalent experience) in computer science, electrical engineering, or a related STEM field with a focus on artificial intelligence.
A proven track record of academic publications in credible conferences or journals, such as ICML, ICLR, NeurIPS, CVPR, ICCV/ECCV, ICRA, IROS.
Nice To Have Skills and Experience :
Experience working with edge devices.
Experience with simulation environments for audio, robotics, or related AI applications.

Requirements:
Bachelors degree in a quantitative field (engineering, statistics, data science, or similar).
5+ years of Product Analytics experience in SaaS environments (healthcare or regulated industries - advantage).
Strong hands-on experience working with large datasets and complex databases, including advanced SQL proficiency and data modeling.
Experience implementing and maintaining product instrumentation and analytics tracking frameworks.
Experience with product analytics tools (e.g., Mixpanel, Amplitude, Heap) and BI tools.
Ability to operate both strategically and technically - connecting business goals with analytical execution and data infrastructure.
Strong analytical mindset with a passion for data-driven product development.
Previous management experience - Advantage
Experience with Qlik - Advantage
Experience with consumer-facing (B2C) products - Advantage

Requirements:
5+ years of hands-on experience with coding ML based solutions in high scale systems
Relevant industry experience / publications in ad-tech and recommender system
Msc/Phd in computer science / math
Industry experience in building engineering at scale
Large-scale distributed systems, service oriented architecture.
Previous experience with all or some of the elements of our Stack (we mainly use Go, Python, Java, AWS, Jupyter notebooks).
Knowledge in data engineering.
Ability to transform raw data into actionable business insights
Please submit your CV in English.

Requirements:
What We Need To See:

BS/MS in AI, Data Science, or a computer science-related field or equivalent experience.

10+ years of overall industry experience in software engineering, developer relations, technical partnerships, or related roles, including 4+ years of hands-on experience in AI and managing a technical team.

Demonstrated experience managing technical collaborations, concentrating on AI.

Strong interpersonal abilities with the capacity to simplify complex technical ideas for a range of technical and non-technical audiences, from engineers to executives.

Proven ability to structure and implement complex technical engagements. You negotiate requirements, prioritize issues, and collaborate with internal or external customers across sales, legal, product, or marketing teams as needed.


Ways to stand out from the crowd:

Established Leadership: Background in directing technical teams and handling developer relations or community engineering initiatives.

Deep AI/ML Domain Expertise: Strong technical competence in GenAI, machine learning frameworks, data science applications, or embedded systems.

Ecosystem Influencer: Deeply connected to the Israeli tech and startup ecosystem.

Matrix Navigator: Ability to function effectively and independently in a complex, fast-paced global matrix organization.

Outstanding Communicator: Ability to simplify complex GPU architecture and SDK capabilities into compelling value propositions for developers and executive collaborators alike.

Requirements:
Youll be a great fit if you have...

5+ years of hands-on experience in data science and machine learning with a proven record of leveraging modeling into business outcomes.
Proficiency in Python and its ML/data stack (e.g., PyTorch or TensorFlow, Pandas, NumPy, Scikit-learn).
Expertise in time-series forecasting, ideally Deep Learning based, preferably in demand prediction or related areas.
Feature engineering, feature importance testing, explainability based experience.
Masters or PhD in Computer Science, Machine Learning, Statistics, Engineering or a relevant field.
Solid understanding of ML production workflows (versioning, testing, reproducibility, and deployment).
Excellent communication and collaboration skills.

Requirements:
8+ years of software engineering experience, including 3+ years in technical leadership, team leadership, or architecture roles.
Solid background in ML & LLM foundations and development methodologies
Solid background in classical software engineering
Proven track record leading cross-functional teams and delivering complex production-grade systems.
Strong understanding of modern software architecture, distributed systems, APIs, cloud-native systems, and scalable application design.
Fluency in fullstack technologies: python, typescript, javascript, SQL, NoSQL
Hands-on experience with LLM-based, AI-assisted, ML-powered, or data-intensive applications.
Practical understanding of RAG, tool calling, structured outputs, prompt/version management, workflow orchestration, agents, and LLM evaluation.
Advanced usage of LLM based coding assistance technologies: claude code, codex, etc.
Experienced and pragmatic code reviewer.
Strong ability to plan, prioritize, and execute across multiple streams of work.
Strong judgment around architecture, reliability, latency, cost, security, data access, and user trust.
Excellent leadership, communication, mentoring, and decision-making skills.
Comfortable working in a fast-moving environment with ambiguity and evolving requirements.

Requirements:
Requirements
Proven experience as a Data Scientist.
Proven experience designing and maintaining large-scale data platforms (hundreds of TBs)
3+ years of proven experience leading and managing a team of data engineers (people management is required)
4+ years of experience in data science, including a strong Python programming background, advanced SQL skills, and data modeling experience
Expertise with data orchestration tools (Airflow, Prefect, or Dagster)
Cloud platform experience - GCP preferred (AWS/Azure acceptable)
Familiarity with Docker
Strong communication, mentorship, and collaboration skills
BSc/MSc in Mathematics/ physics/ statistics/ Computer Science.
Fluent English (spoken and written)