דרושים » ניהול ביניים » Senior Data Scientist

we are looking for a ML Engineer.
As a Senior ML Infrastructure Engineer, you will design and build the infrastructure that powers our ML and LLM systems in production. You will develop scalable pipelines, systems, and tools that enable data scientists and AI teams to efficiently develop, test, and deploy models.
Working closely with data scientists, engineers, and product teams, you will ensure our ML capabilities are reliable, scalable, and production-ready-helping bring cutting-edge AI to improve mental health care.
This is a unique opportunity to join a startup with a real impact on thousands of peoples wellbeing and mental health, applying cutting-edge AI technologies to solve meaningful human problems.

We are looking for a visionary and technically versatile Data Science Manager to join the Data Science & MLE group within our DS & Analytics organization.
In this pivotal role, you will lead a hybrid team of Data Scientists and Machine Learning Engineers, acting as the bridge between cutting-edge technical innovation and high-level business strategy. You won't just be managing a team; you will be the Technical Lead defining how we solve complex problems-from predicting player behavior to optimizing marketing budgets using the latest in Generative AI.
You will partner closely with Game Directors, Product Managers, and our central analytics teams to drive value across Zynga's diverse portfolio. If you are a leader who is "bilingual" in data-possessing deep Data Science expertise to guide methodology while bringing high MLE and Engineering skills to build scalable, production-ready systems-we want to hear from you.
Key Responsibilities:
Team Leadership & Mentorship: Recruit, retain, and develop top-tier talent within the Data Science & MLE team. Foster an inclusive culture of innovation where technical rigor meets creative problem-solving.

Technical Direction & Engineering Standards: Act as the hands-on Technical Lead for the domain. You will supervise the end-to-end development lifecycle-from research to production-enforcing high standards and MLOps to ensure our models are scalable and maintainable.
Strategic DS & Analytics Support: Drive the development of advanced analytical frameworks to solve core business challenges. You will guide the team in applying rigorous statistical and machine learning methods to areas such as Time Series Forecasting, Causal Inference, Marketing Optimization, Root Cause Analysis, and more.
Strategy & Collaboration: Partner with Game Directors, BI Platform PMs, and embedded analytics teams to define the data strategy and roadmap. You will ensure that our technical initiatives are directly aligned with company-wide goals and solving the right problems.
Global Alignment: Maintain a tight collaborative network with Data Science & Analytics managers in North America, ensuring global consistency in methodologies, knowledge sharing, and joint development.

As a Data Scientist in our company, you will be a part of a large and innovative data science group, working closely with Dev teams and product managers, to create business value through Data Science and Machine Learning methods using cutting edge technology, on large and diverse datasets.
The Role consists of understanding customers' needs and product requirements, exploring data, identifying and defining functionality from conception to delivery, creating and improving algorithms and ML pipelines, building measurement tools, providing data visualizations, and more.
Deliver end-to-end ML products - including data processing, problem analysis, research, model development, validation and metrics, implemented in production and with online testing.

Were looking for a Senior Data Scientist who will join our growing Detection group. You'll be a significant part of the development of our state-of-the-art anomaly detection models to find and protect against nation-sponsored cyber-attacks. In this role, you will work with product, engineering, and cyber teams to train, evaluate, and deploy anomaly detection models on a massive scale.
The Dream-Maker Responsibilities
Analyze, transform and clean large, complex data sets from various sources to ensure data quality and integrity for analysis.
Conduct hands-on research and development of state-of-the-art models and algorithms.
Extract relevant features from structured and unstructured data sources, design and engineer new features and feature selection methodologies to enhance model performance.
Build, train, and optimize machine learning models using state-of-the-art techniques, and evaluate model performance using appropriate metrics.
Lead research projects end-to-end from problem formulation, ideation, and experimental design to prototyping and transition into production.
Explore new methodologies and develop creative approaches to solve complex challenges.

Required Customer-Facing Data Scientist - Demand Forecasting
HQ in Tel Aviv with a growing sales and marketing organization in the US
Customers across CPG, retail, healthcare, mobile apps, fintech, insurance, and consumer services. Marquee customers include Johnson & Johnson, Mars, and SciPlay.
Demand Forecasting Team:
The Demand Forecasting team is at a pivotal, high-growth stage. We have successfully built our core pipeline and are now aggressively onboarding new, diverse customers. This role is highly dynamic, requiring a blend of technical depth, proactive research, and exceptional communication to adapt our platform to real-world customer data and challenges. You will be a critical link between the core product and our clients business success.
Responsibilities:
As a key Customer-Facing Data Scientist on the Demand Forecasting team, you will:
Work at the forefront of the data world, focusing on the optimization and deployment of Demand Forecasting models.
Handle complex data science challenges using state-of-the-art techniques relevant to demand forecasting and time series, such as forecasting model ensembling, anomaly detection, feature engineering for trend/seasonality, and causal inference modeling.
Act as a highly communicative partner to our clients, diving deep into their unique datasets to understand the nuances and challenges of their business.
Lead the rigorous testing and application of our core ML pipeline on new customer data, identifying areas where it performs exceptionally well and researching/developing solutions for complex cases where it does not.
Be instrumental in helping our clients achieve their business goals and realize the measurable value of our Demand Forecasting module.
Work within a production and product-oriented environment, ensuring models are robust, scalable, and directly integrated into the clients operational workflow.

SuperSonic is looking for a passionate Senior Data Scientist, to work end to end on some of our core problems. Solving these will help drive revenue and improve decision making.
As a Senior Data Scientist you will be handed a business problem and will be asked to provide an end to end solution - Unpack and thoroughly understand the business problem, define the strategy to deal with it and develop & deploy your solution along with relevant support.
What you'll be doing
Design and implement end-to-end solutions - from business needs all the way to live deployment
Monitor and own models in production
Model, design, and implement machine learning and data mining algorithms
Perform deep data analysis to evaluate performance and recommend improvements
Help, guide and support our business partners to allow for scale and accuracy while adopting your solutions.

we are looking for a Senior Data Scientist to build and deploy time series forecasting and classical machine learning models that support core business planning and operational decisions. You will own problems end-to-end, from data exploration and feature engineering to model deployment and monitoring, working with large-scale, real-world datasets.
The role emphasizes strong statistical thinking, robust modeling, and production reliability over experimentation with trendy frameworks. Your work will directly impact forecasting accuracy, resource planning, and key business metrics.
Youre welcome to work in our offices in Tel Aviv.
Your responsibilities will include:
Time series forecasting. Design, build, and maintain forecasting models (e.g., demand, usage, capacity). Evaluate performance using appropriate metrics and improve accuracy over time.
Classical ML modeling. Develop and deploy models using regression,Binary classifcatiom , tree-based methods, and other well-established approaches where they provide the best trade-off between performance, interpretability, and maintainability.
Feature engineering & data preparation. Build robust pipelines for data cleaning, transformation, and feature generation (including time-based features, seasonality, and external signals).
Model evaluation & monitoring.Define evaluation frameworks, backtesting strategies, and monitoring to ensure models remain stable and reliable in production.
Production & MLOps. Deploy models into production environments, collaborate on pipeline orchestration, and ensure reproducibility and version control.
Exploratory analysis. Analyze large datasets to identify patterns, anomalies, and drivers of change in time-dependent behavior.
Stakeholder collaboration. Work closely with business and product teams to define forecasting needs, align on success metrics, and translate model outputs into actionable insights.
Cross-domain contribution. Contribute to adjacent data science areas (e.g., LLM-based systems) as needed, ensuring shared ownership and continuity across team responsibilities.

We are seeking a Senior Data Scientist / Applied Researcher to build the next generation of AI models powering diverse cybersecurity use cases across our products and organization. This role involves significant work with large language models (LLMs) and advanced machine learning techniques to tackle complex, real-world challenges. You will lead and drive the company's innovation strategy, translating cutting-edge research into measurable business impact and shaping the future direction of our AI capabilities.
The Dream-Maker Responsibilities
Conduct hands-on research and development of state-of-the-art models, algorithms, and systems.
Lead research projects end-to-end from problem formulation, ideation, and experimental design to prototyping and transition into production.
Explore new methodologies and develop creative approaches to solve complex challenges.
Identify ambitious research directions and invent novel approaches to solve complex, high-impact problems.
Shape the research roadmap and influence long-term technical strategy across the organization.

Realize your potential by joining the leading performance-driven advertising company!
As a Senior MLOps Engineer on the Infra group, youll play a vital role in develop, enhance and maintain highly scalable Machine-Learning infrastructures and tools.
How youll make an impact:
As a Senior MLOps Engineer Engineer, youll bring value by:
Develop, enhance and maintain highly scalable Machine-Learning infrastructures and tools, including CI/CD, monitoring and alerting and more
Have end to end ownership: Design, develop, deploy, measure and maintain our machine learning platform, ensuring high availability, high scalability and efficient resource utilization
Identify and evaluate new technologies to improve performance, maintainability, and reliability of our machine learning systems
Work in tandem with the engineering-focused and algorithm-focused teams in order to improve our platform and optimize performance
Optimize machine learning systems to scale and utilize modern compute environments (e.g. distributed clusters, CPU and GPU) and continuously seek potential optimization opportunities.
Build and maintain tools for automation, deployment, monitoring, and operations.
Troubleshoot issues in our development, production and test environments
Influence directly on the way billions of people discover the internet.

we are looking for a Senior Data Scientist (Applied AI / LLM) to design, build, and deploy production-grade AI systems based on large language models. You will focus on turning LLM capabilities into reliable, measurable business solutions, while also contributing to predictive modeling across different business domains.
Your work will include building evaluation frameworks, improving model accuracy, and developing agent-based systems that automate analytical and data workflows (e.g., data quality monitoring). The role emphasizes production readiness, robustness, and real business impact-not experimentation.
Youre welcome to work in our office in Tel Aviv.
Your responsibilities will include:
LLM system development. Design and deploy LLM-based solutions (e.g., RAG pipelines, agent workflows) for real business use cases.
Evaluation & reliability. Build evaluation frameworks to measure accuracy, consistency, and failure modes of LLM systems. Continuously improve performance based on real-world usage.
Agent-based automation. Develop agentic solutions to automate workflows such as data quality checks, anomaly detection, and reporting.
Applied predictive modeling. Apply classical ML and statistical methods to business domains such as HR and Finance (e.g., forecasting, classification, risk modeling).
Production & MLOps. Deploy and maintain models in production, ensuring monitoring, versioning, and scalability.
Stakeholder collaboration. Translate business needs into AI/ML solutions and communicate trade-offs, risks, and performance clearly.
Cross-domain contribution. Contribute to adjacent areas (e.g., forecasting models) to ensure team redundancy and shared ownership of critical workflows.