לוח משרות דרושים Senior Data Scientist, לחיפוש זה נמצאו 33 משרות

Requirements:
Minimum qualifications
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).
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).
An M.S. or Ph.D. degree in computer science, statistics, or related field OR equivalent work experience.
Preferred qualifications:
Experience with distributed cloud systems and 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 cybersecurity principles, attack vectors, and defense mechanisms.
Excellent communication (both written and verbal) and presentation skills.
Ability to work independently in a fast-paced environment and come up with creative solutions to challenging problems.

Requirements:
M.Sc. or Ph.D. in Computer Science, Statistics, Mathematics, or related field.
6+ years of hands-on data science experience, including direct work with lifecycle marketing, personalization, or customer analytics.
Advanced expertise in statistics, causal inference, and experimental design.
Proven track record of implementing reinforcement learning / multi-armed bandit models in production.
Strong software engineering skills in Python, SQL, and ML frameworks
Exceptional communication skills - able to influence internal teams and present to executive-level customers.
Entrepreneurial mindset: thrives in uncertainty, challenges assumptions, and pushes for impactful solutions.

Requirements:
Education: MSc or PhD in Data Science, Computer Science, Mathematics, Statistics, or a related engineering field.
Experience: 4+ years of proven experience as a Data Scientist solving complex business problems with state-of-the-art algorithms.
Deep Learning: Hands-on experience with deep learning frameworks (e.g., PyTorch, TensorFlow, Keras).
Engineering & Production: High-level software engineering expertise, with a strong track record of deploying, maintaining, and scaling models in rigorous production environments.
Strong analytical thinking: Take a vague business question, translate it into a testable hypothesis, build the infrastructure to run an experiment, and draw rigorous conclusions from the results.
Massive Scale: Experience working with billions of records and big-data frameworks (e.g., Spark, Ray, Dask, Airflow).
Domain Expertise: Proven experience building and optimizing applied recommendation systems.
AI development: Fluency with modern AI coding tools and practices (e.g. Cursor, Claude Code, Copilot) and an eagerness to integrate them into your daily workflow
Leadership & Soft Skills: Demonstrated experience leading machine learning projects. You are a highly analytical team player capable of handling multiple tasks simultaneously in a fast-paced environment.
You might also have
LLM & Agentic Frameworks: Experience building applications with modern AI tools and frameworks (e.g., LangChain, LangGraph).
AI Observability: Hands-on experience with LLM observability, evaluation, and tracing frameworks (e.g., Langfuse).
MLOps & Infra: Experience working with MLOps tools (e.g., MLflow, Kubeflow, Weights & Biases, SageMaker) and feature stores (e.g., Feast, Tecton).
Additional information
Relocation support is not available for this position
Work visa/immigration sponsorship is not available for this position
Benefits
At our company, we want our team members to thrive. We offer a wide range of benefits designed to support well-being and work-life balance.

Requirements:
4+ years of experience building machine learning solutions end-to-end, from research and experimentation through production.
MSc or PhD in Computer Science, Mathematics, Statistics, Engineering, or a related quantitative field.
Experience developing machine learning models for real-time bidding (RTB), recommendation systems, ranking, pricing, or other large-scale optimization problems.
Strong programming skills in Python and experience working with production-grade machine learning systems.
Strong foundation in machine learning, statistical modeling, experimentation, and data analysis.
Bonus points if you have:
Experience with deep learning models in large-scale recommendation or advertising systems.
Experience using AI development tools (such as Claude Code or Cursor) to accelerate experimentation and development.

Requirements:
8+ years in data science or quantitative analysis, ideally in AdTech, marketplaces, or consumer-scale products
Strong foundations in experimental design, hypothesis testing, causal inference, and statistical/ML modeling (regression, classification, clustering, time-series)
Fluency in SQL and Python (or R), and comfort working with large-scale data in cloud data warehouses / lakes
Distinctive problem-solving skills and the ability to translate analysis into business recommendations
Excellent written and verbal communication, including the ability to influence senior stakeholders
Nice to have
Experience with Databricks, Spark, or semantic-layer / metrics platforms
Background in bidding, auctions, recommendation, or measurement/attribution
Experience standing up experimentation tooling or analytics infrastructure.

Requirements:
Who You Are:
Have AdTech experience and understand the thrill of low-latency environments and high-stakes auction dynamics
The Scientist-Engineer Hybrid: You have a 5+ year track record of delivering DS projects to production. An MSc/PhD in a quantitative field is a must
Tech Mastery: Expert-level Python (production-grade) and the ability to build for scale (Spark, ONNX - great advantage)
The "Nose for Value": You are business-oriented and independent
You don't just solve equations; you solve business problems and know how to measure your success
Mentor & Partner: You lead by example, elevating the teams technical bar through code reviews and collaborative design.