Data Scientist jobs in Netanya

Description Fetcherr builds responsible AI that turns market complexity into measurable profit growth. At its core is the Market Model, a proprietary AI model that delivers granular demand predictions and real-time decision intelligence for commercial teams. Built on a glass-box architecture, it uses market data, not personal data, with full transparency into logic and outcomes. First deployed in global aviation, the technology is industry-agnostic, and Fetcherr delivers a consistent average profit uplift of 7%. Fetcherr Labs is a new unit that takes this engine to mid-size companies, run by agents and delivered inside the tools customers already use, such as Excel and Copilot. Labs is small, flat and senior, and builds with AI agents from day one. You will work directly with the Market Model Lead and report to the Chief of Labs. The role We are looking for a Demand Modeling Scientist who owns demand models end to end: from a new customer's raw history to a model running in production, measured against real outcomes. You will teach the engine how demand behaves in new industries, starting with aftermarket parts, and prove the uplift through live A/B tests with our design partners. What you'll do • Develop and implement state-of-the-art econometric and machine learning models for demand forecasting. • Own the full machine learning lifecycle: data exploration, feature engineering, training, validation, deployment, monitoring, retraining and retirement. • Conduct research and experimentation to improve accuracy, robustness and scalability, and adapt models to new industries and customer data. • Design how models are measured in production, including A/B tests that show the uplift for each customer. • Build with AI coding agents as your everyday way of working: agents write and test much of the code, and you design, review and decide. • Work with data and platform engineers to put models into production on Azure, and keep them explainable and reliable. • Explain complex findings clearly to non-technical stakeholders, including customers and executives. Requirements What you bring • 5+ years of hands-on experience in data science and machine learning, with a proven record of turning models into business outcomes. • Proven experience taking models through the full lifecycle into production: versioning, testing, reproducibility, deployment, monitoring and retraining. • Expertise in time-series forecasting, ideally deep-learning based, preferably in demand prediction or related areas. • Feature engineering, feature importance testing and explainability experience. • Proficiency in Python and its ML and data stack (PyTorch or TensorFlow, Pandas or Polars, NumPy, Scikit-learn, SQL). • Hands-on use of AI coding agents (such as Claude Code or GitHub Copilot) in your daily development, and a strong view on where they help and where they don't. • Master's or PhD in Computer Science, Machine Learning, Statistics, Engineering or a related field. • Excellent communication and collaboration skills. Nice to have • Experience with pricing, revenue management, retail or B2B distribution. • Experience with experimentation and causal measurement (A/B testing, uplift). • Experience with cloud ML platforms (Azure ML or Microsoft Fabric preferred; GCP or AWS also relevant). • Familiarity with workflow orchestration in general (any modern orchestrator). • Publications in top-tier peer-reviewed ML venues (ICLR, ICML, NeurIPS) or strong results in data science competitions. If you want to own demand models end to end, build with agents, and bring a proven AI engine to a whole new market, we'd love to hear from you.

Description Fetcherr builds responsible AI that transforms market complexity into measurable profit growth. At the core of the company is the Market Model - a proprietary AI-powered model delivering accurate, granular demand predictions with 96% forecast accuracy and real-time decision intelligence for commercial teams. Built on a glass-box architecture, it uses market data - not personal data - with full transparency into logic and outcomes. First deployed in global aviation, the technology is industry-agnostic and scales across volatile markets. Fetcherr delivers a consistent average profit uplift of 7%, with corporate partners including Delta, Virgin Atlantic, WestJet, Viva, and Azul. The Large Market Modeling (LMM) team is the engine underneath Fetcherr's pricing intelligence. We're the ones who actually build and train the models — taking a chaotic world of market signals, customer behavior, and competitive dynamics and turning them into reliable, production-ready demand models. Other teams at Fetcherr work with the models; we're the ones who bring them to life. Think of us as the team that teaches Fetcherr's AI how people buy — so it can always recommend the right price at the right moment. We are seeking a talented and self-driven experienced Data Scientist to help advance our machine learning capabilities.This is a key role for someone passionate about leveraging machine learning to solve complex, real-world problems and deliver measurable business impact. Responsibilities: • Develop and implement state-of-the-art econometric and machine learning models for demand forecasting. • Conduct research and experimentation to evaluate novel approaches for improving accuracy, robustness, and scalability. • Collaborate with cross-functional teams (including product, data engineering, MLOPS and Platform) to deploy ML systems in production. • Clearly communicate complex technical findings to non-technical stakeholders, including product leaders and executives. Requirements • 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. • Master’s 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. Nice to have: • Publications in top-tier, peer-reviewed ML/AI venues (e.g. ICLR, ICML, NIPS, etc.) • Experience applying ML in domains like finance, trading, revenue management etc. • Familiarity with cloud based solutions on GCP platform (e.g., Vertex AI, PubSub, Cloud Run Functions). • Strong data visualization and exploratory data analysis skills. • Familiarity with code optimization, containerization (e.g., Docker), CI/CD, or cloud-native architectures. • Participation in competitive programming or data science challenges (e.g., Kaggle). If you're excited about building impactful AI systems in a high-growth startup environment, and want to help redefine how industries price, forecast, and optimize, we’d love to hear from you.

Description Fetcherr builds responsible AI that transforms market complexity into measurable profit growth. At the core of the company is the Market Model - a proprietary AI-powered model delivering accurate, granular demand predictions with 96% forecast accuracy and real-time decision intelligence for commercial teams. Built on a glass-box architecture, it uses market data - not personal data - with full transparency into logic and outcomes. First deployed in global aviation, the technology is industry-agnostic and scales across volatile markets. Fetcherr delivers a consistent average profit uplift of 7%, with corporate partners including Delta, Virgin Atlantic, WestJet, Viva, and Azul. The Large Market Model group (LMM) is looking for a Director of Data Science to lead its production engineering, overseeing MLOps, ML engineering and Data engineering. The Director owns the end to end ML lifecycle of the market model, from the data pipelines that feed it, through model training and serving, and on to the monitoring that keeps it healthy once it is live in customer systems. Crucially, the Director is responsible for setting the roadmap across these functions, alongside LMM management and senior executives, and for turning it into work each function can execute. We are looking for a manager who has led high paced, AI first groups, and who has carried deliveries for systems running live in front of customers. RESPONSIBILITIES • Decide priorities across the functions with their leads, and review the technical trade-offs yourself. • Manage the leads who run these functions and hold each of them to what their team has committed to. • Stay close to production. Own delivery dates, reliability, and what happens when something breaks. • Own the infrastructure for model training, serving, and large scale data processing, including its cost. • Decide which numbers (KPIs) the group is measured on, then track them and report them. • Report the group's progress and risks to senior management, to product, and to the commercial teams. • Work with the applied research team to move their results into production. • Hire and keep senior engineers, and decide how the group is staffed. • Set the engineering standards the group works to: CI/CD, automated testing, observability, and model monitoring. Requirements You'll be a great fit if you have: • 8+ years in engineering, with 5+ years leading teams and managers. • Worked in a multi group environment, leading projects that involve inter group dependencies • Production experience with time series forecasting, reinforcement learning, or large scale optimization. • Experience setting the direction for a machine learning or data engineering group • Enough depth in production ML systems to review architecture decisions with your senior engineers. • Experience holding managers to delivery dates and to the numbers their teams are measured on. • Hands-on familiarity with Python, PyTorch, Google Cloud Platform (GCP), and orchestration frameworks such as Dask and Dagster. • A Bachelor's degree in Computer Science, Engineering, Mathematics, or a relevant field. • The ability to explain a technical decision to a commercial audience, and a commercial constraint to your engineers. NICE TO HAVE • An MSc or PhD in Computer Science, Machine Learning, Statistics, Engineering, or a relevant field. • Experience taking a machine learning platform from an early prototype to something a business runs on. • Experience in airlines, travel, revenue management, or dynamic pricing. • Familiarity with real time inference and high volume data processing. If you want to run the engineering group behind models that set real prices in real markets, we'd like to hear from you.

Description Fetcherr builds responsible AI that transforms market complexity into measurable profit growth. At the core of the company is the Market Model - a proprietary AI-powered model delivering accurate, granular demand predictions with 96% forecast accuracy and real-time decision intelligence for commercial teams. Built on a glass-box architecture, it uses market data - not personal data - with full transparency into logic and outcomes. First deployed in global aviation, the technology is industry-agnostic and scales across volatile markets. Fetcherr delivers a consistent average profit uplift of 7%, with corporate partners including Delta, Virgin Atlantic, WestJet, Viva, and Azul. We're looking for a Data Scientist to help us grow our advanced analytics team's capabilities. The ideal candidate is a data scientist with a relevant experience who is self-driven, motivated, independent and sharp • Design and operationalize causal-uplift measurement frameworks to quantify the incremental impact of pricing models • Lead data discovery and translate complex multidimensional data into actionable insights related to the pricing algorithms and their outcomes • Conduct research and experimentation to elaborate novel approaches to uplift measuring and a/b testing • Collaborate with revenue managers, data analysts, data engineers in order to encode airline business logic into modeling and technical pipelines At Fetcherr, the Insights & Decision Science (IDS) team is where data meets storytelling. We take the hard work of our AI pricing engine and translate it into something airlines can actually see, trust, and act on — think rigorous statistical analysis with a human touch. If a number moves, we explain why. If a client has a question, we have the answer (and the chart to back it up). Requirements * You have at least 5 years of hands-on data analytics & science experience with proven record of leveraging modeling into business insights * You are proficient in Python (typical data analytics and machine learning stack: pandas, numpy, scikit, statsmodels) * You know to assess the performance and impact of the ML-powered system from business environments perspective * You have great communication and storytelling skills to both technical and non-technical audiences (ability to present to C level stakeholders executives as well) *You are experienced in translating complex client requirements into actionable insights, and ability to present findings and strategies to stakeholders *You are able to provide and recommend innovative solutions and approaches to non-trivial challenges *You’re a team player, ready to help others meeting aggressive timelines and motivate the team to meet the product deadlines *B.SC or Master’s degree in Economy / Statistics / Math or similar (Phd is a plus) You are proficient in using SQL (BigQuery / Dataform / GCP experience is a plus) and git Great if you have them: • Domain knowledge in following industries: airlines, transportation, logistics or vacations • Experience with causal inference, uplift modeling, anomaly detection or pricing algorithms • Knowledge in mathematical optimization